EASD 2014

VIENNA – Treatment with an insulin pump rather than insulin injections may help protect patients with type 2 diabetes from heart disease, a large registry study has determined.

Over a mean follow-up of about 7 years, the pump was associated with a 44% decrease in the risk of fatal cardiovascular disease. It also conferred a 29% decrease in the risk of death overall, Dr. Soffia Gudbjornsdottir said at the annual meeting of the European Association for the Study of Diabetes.

She used data extracted from the Swedish National Diabetes Registry, which was founded in 2005. It contains information on 95% of the country’s type 1 diabetes patients and is linked with national inpatient and death registries.

The study group comprised 18,168 patients, 2,441 of whom were using an insulin pump. There were some significant baseline differences between the pump users and the users of injectable insulin.

Pump users were younger (age at baseline 38 vs. 41 years), and more likely to be women. Those treated with the pump had better measures of blood pressure and lipids. They were more likely to exercise and less likely to smoke. Insulin injection users had higher rates of prior cardiovascular disease. However, a propensity matching score eliminated these differences and balanced the group, Dr. Gudbjornsdottir noted.

By 7 years, there had been few cardiovascular events or deaths – an expected finding, since the cohort was young. Fatal/nonfatal coronary heart disease had developed in 7% of the insulin injection users and 4% of the of pump users, a nonsignificant difference. Neither were there significant differences in fatal or nonfatal cardiovascular disease (8% vs. 5%) or noncardiovascular mortality (4% vs. 2%).

However, significant differences did appear in two other endpoints: fatal cardiovascular disease (3% vs. 1%) and total mortality (7% vs. 3%).

A multivariate regression model found several significant risk reductions associated with pump use, including fatal cardiovascular disease (hazard ratio, 0.56), and all-cause mortality (HR, 0.71).

There were no significant differences in the risks for fatal/nonfatal coronary heart disease, fatal/nonfatal cardiovascular disease, or noncardiovascular death.

During the discussion, Dr. Gudbjornsdottir addressed the concern of a treatment allocation bias due to some unknown variable in the group. “If we had such an unknown covariate, with, for example, a hazard ratio of 1.3, it would have had to be present in at least 80% of the insulin group and in none of the pump group to invalidate the results, so I would say our study findings are quite robust.”

She had no financial disclosures.

VIENNA – Treatment with an insulin pump rather than insulin injections may help protect patients with type 2 diabetes from heart disease, a large registry study has determined.

Over a mean follow-up of about 7 years, the pump was associated with a 44% decrease in the risk of fatal cardiovascular disease. It also conferred a 29% decrease in the risk of death overall, Dr. Soffia Gudbjornsdottir said at the annual meeting of the European Association for the Study of Diabetes.

She used data extracted from the Swedish National Diabetes Registry, which was founded in 2005. It contains information on 95% of the country’s type 1 diabetes patients and is linked with national inpatient and death registries.

The study group comprised 18,168 patients, 2,441 of whom were using an insulin pump. There were some significant baseline differences between the pump users and the users of injectable insulin.

Pump users were younger (age at baseline 38 vs. 41 years), and more likely to be women. Those treated with the pump had better measures of blood pressure and lipids. They were more likely to exercise and less likely to smoke. Insulin injection users had higher rates of prior cardiovascular disease. However, a propensity matching score eliminated these differences and balanced the group, Dr. Gudbjornsdottir noted.

By 7 years, there had been few cardiovascular events or deaths – an expected finding, since the cohort was young. Fatal/nonfatal coronary heart disease had developed in 7% of the insulin injection users and 4% of the of pump users, a nonsignificant difference. Neither were there significant differences in fatal or nonfatal cardiovascular disease (8% vs. 5%) or noncardiovascular mortality (4% vs. 2%).

However, significant differences did appear in two other endpoints: fatal cardiovascular disease (3% vs. 1%) and total mortality (7% vs. 3%).

A multivariate regression model found several significant risk reductions associated with pump use, including fatal cardiovascular disease (hazard ratio, 0.56), and all-cause mortality (HR, 0.71).

There were no significant differences in the risks for fatal/nonfatal coronary heart disease, fatal/nonfatal cardiovascular disease, or noncardiovascular death.

During the discussion, Dr. Gudbjornsdottir addressed the concern of a treatment allocation bias due to some unknown variable in the group. “If we had such an unknown covariate, with, for example, a hazard ratio of 1.3, it would have had to be present in at least 80% of the insulin group and in none of the pump group to invalidate the results, so I would say our study findings are quite robust.”

She had no financial disclosures.

VIENNA – Treatment with an insulin pump rather than insulin injections may help protect patients with type 2 diabetes from heart disease, a large registry study has determined.

Over a mean follow-up of about 7 years, the pump was associated with a 44% decrease in the risk of fatal cardiovascular disease. It also conferred a 29% decrease in the risk of death overall, Dr. Soffia Gudbjornsdottir said at the annual meeting of the European Association for the Study of Diabetes.

She used data extracted from the Swedish National Diabetes Registry, which was founded in 2005. It contains information on 95% of the country’s type 1 diabetes patients and is linked with national inpatient and death registries.

The study group comprised 18,168 patients, 2,441 of whom were using an insulin pump. There were some significant baseline differences between the pump users and the users of injectable insulin.

Pump users were younger (age at baseline 38 vs. 41 years), and more likely to be women. Those treated with the pump had better measures of blood pressure and lipids. They were more likely to exercise and less likely to smoke. Insulin injection users had higher rates of prior cardiovascular disease. However, a propensity matching score eliminated these differences and balanced the group, Dr. Gudbjornsdottir noted.

By 7 years, there had been few cardiovascular events or deaths – an expected finding, since the cohort was young. Fatal/nonfatal coronary heart disease had developed in 7% of the insulin injection users and 4% of the of pump users, a nonsignificant difference. Neither were there significant differences in fatal or nonfatal cardiovascular disease (8% vs. 5%) or noncardiovascular mortality (4% vs. 2%).

However, significant differences did appear in two other endpoints: fatal cardiovascular disease (3% vs. 1%) and total mortality (7% vs. 3%).

A multivariate regression model found several significant risk reductions associated with pump use, including fatal cardiovascular disease (hazard ratio, 0.56), and all-cause mortality (HR, 0.71).

There were no significant differences in the risks for fatal/nonfatal coronary heart disease, fatal/nonfatal cardiovascular disease, or noncardiovascular death.

During the discussion, Dr. Gudbjornsdottir addressed the concern of a treatment allocation bias due to some unknown variable in the group. “If we had such an unknown covariate, with, for example, a hazard ratio of 1.3, it would have had to be present in at least 80% of the insulin group and in none of the pump group to invalidate the results, so I would say our study findings are quite robust.”

She had no financial disclosures.

VIENNA – Treatment with an insulin pump rather than insulin injections may help protect patients with type 2 diabetes from heart disease, a large registry study has determined.

Over a mean follow-up of about 7 years, the pump was associated with a 44% decrease in the risk of fatal cardiovascular disease. It also conferred a 29% decrease in the risk of death overall, Dr. Soffia Gudbjornsdottir said at the annual meeting of the European Association for the Study of Diabetes.

She used data extracted from the Swedish National Diabetes Registry, which was founded in 2005. It contains information on 95% of the country’s type 1 diabetes patients and is linked with national inpatient and death registries.

The study group comprised 18,168 patients, 2,441 of whom were using an insulin pump. There were some significant baseline differences between the pump users and the users of injectable insulin.

Pump users were younger (age at baseline 38 vs. 41 years), and more likely to be women. Those treated with the pump had better measures of blood pressure and lipids. They were more likely to exercise and less likely to smoke. Insulin injection users had higher rates of prior cardiovascular disease. However, a propensity matching score eliminated these differences and balanced the group, Dr. Gudbjornsdottir noted.

By 7 years, there had been few cardiovascular events or deaths – an expected finding, since the cohort was young. Fatal/nonfatal coronary heart disease had developed in 7% of the insulin injection users and 4% of the of pump users, a nonsignificant difference. Neither were there significant differences in fatal or nonfatal cardiovascular disease (8% vs. 5%) or noncardiovascular mortality (4% vs. 2%).

However, significant differences did appear in two other endpoints: fatal cardiovascular disease (3% vs. 1%) and total mortality (7% vs. 3%).

A multivariate regression model found several significant risk reductions associated with pump use, including fatal cardiovascular disease (hazard ratio, 0.56), and all-cause mortality (HR, 0.71).

There were no significant differences in the risks for fatal/nonfatal coronary heart disease, fatal/nonfatal cardiovascular disease, or noncardiovascular death.

During the discussion, Dr. Gudbjornsdottir addressed the concern of a treatment allocation bias due to some unknown variable in the group. “If we had such an unknown covariate, with, for example, a hazard ratio of 1.3, it would have had to be present in at least 80% of the insulin group and in none of the pump group to invalidate the results, so I would say our study findings are quite robust.”

She had no financial disclosures.

[email protected]

On Twitter @alz_gal

VIENNA – Treatment with an insulin pump rather than insulin injections may help protect patients with type 2 diabetes from heart disease, a large registry study has determined.

Over a mean follow-up of about 7 years, the pump was associated with a 44% decrease in the risk of fatal cardiovascular disease. It also conferred a 29% decrease in the risk of death overall, Dr. Soffia Gudbjornsdottir said at the annual meeting of the European Association for the Study of Diabetes.

She used data extracted from the Swedish National Diabetes Registry, which was founded in 2005. It contains information on 95% of the country’s type 1 diabetes patients and is linked with national inpatient and death registries.

The study group comprised 18,168 patients, 2,441 of whom were using an insulin pump. There were some significant baseline differences between the pump users and the users of injectable insulin.

Pump users were younger (age at baseline 38 vs. 41 years), and more likely to be women. Those treated with the pump had better measures of blood pressure and lipids. They were more likely to exercise and less likely to smoke. Insulin injection users had higher rates of prior cardiovascular disease. However, a propensity matching score eliminated these differences and balanced the group, Dr. Gudbjornsdottir noted.

By 7 years, there had been few cardiovascular events or deaths – an expected finding, since the cohort was young. Fatal/nonfatal coronary heart disease had developed in 7% of the insulin injection users and 4% of the of pump users, a nonsignificant difference. Neither were there significant differences in fatal or nonfatal cardiovascular disease (8% vs. 5%) or noncardiovascular mortality (4% vs. 2%).

However, significant differences did appear in two other endpoints: fatal cardiovascular disease (3% vs. 1%) and total mortality (7% vs. 3%).

A multivariate regression model found several significant risk reductions associated with pump use, including fatal cardiovascular disease (hazard ratio, 0.56), and all-cause mortality (HR, 0.71).

There were no significant differences in the risks for fatal/nonfatal coronary heart disease, fatal/nonfatal cardiovascular disease, or noncardiovascular death.

During the discussion, Dr. Gudbjornsdottir addressed the concern of a treatment allocation bias due to some unknown variable in the group. “If we had such an unknown covariate, with, for example, a hazard ratio of 1.3, it would have had to be present in at least 80% of the insulin group and in none of the pump group to invalidate the results, so I would say our study findings are quite robust.”

She had no financial disclosures.

[email protected]

On Twitter @alz_gal

VIENNA – Treatment with an insulin pump rather than insulin injections may help protect patients with type 2 diabetes from heart disease, a large registry study has determined.

Over a mean follow-up of about 7 years, the pump was associated with a 44% decrease in the risk of fatal cardiovascular disease. It also conferred a 29% decrease in the risk of death overall, Dr. Soffia Gudbjornsdottir said at the annual meeting of the European Association for the Study of Diabetes.

She used data extracted from the Swedish National Diabetes Registry, which was founded in 2005. It contains information on 95% of the country’s type 1 diabetes patients and is linked with national inpatient and death registries.

The study group comprised 18,168 patients, 2,441 of whom were using an insulin pump. There were some significant baseline differences between the pump users and the users of injectable insulin.

Pump users were younger (age at baseline 38 vs. 41 years), and more likely to be women. Those treated with the pump had better measures of blood pressure and lipids. They were more likely to exercise and less likely to smoke. Insulin injection users had higher rates of prior cardiovascular disease. However, a propensity matching score eliminated these differences and balanced the group, Dr. Gudbjornsdottir noted.

By 7 years, there had been few cardiovascular events or deaths – an expected finding, since the cohort was young. Fatal/nonfatal coronary heart disease had developed in 7% of the insulin injection users and 4% of the of pump users, a nonsignificant difference. Neither were there significant differences in fatal or nonfatal cardiovascular disease (8% vs. 5%) or noncardiovascular mortality (4% vs. 2%).

However, significant differences did appear in two other endpoints: fatal cardiovascular disease (3% vs. 1%) and total mortality (7% vs. 3%).

A multivariate regression model found several significant risk reductions associated with pump use, including fatal cardiovascular disease (hazard ratio, 0.56), and all-cause mortality (HR, 0.71).

There were no significant differences in the risks for fatal/nonfatal coronary heart disease, fatal/nonfatal cardiovascular disease, or noncardiovascular death.

During the discussion, Dr. Gudbjornsdottir addressed the concern of a treatment allocation bias due to some unknown variable in the group. “If we had such an unknown covariate, with, for example, a hazard ratio of 1.3, it would have had to be present in at least 80% of the insulin group and in none of the pump group to invalidate the results, so I would say our study findings are quite robust.”

She had no financial disclosures.

[email protected]

On Twitter @alz_gal

VIENNA – Most of the increased risk of cancer associated with diabetes appears in the first year or so after diabetes diagnosis, suggesting that it’s mainly attributable to increased medical surveillance.

Three studies presented at the annual meeting of the European Association for the Study of Diabetes came to similar conclusions, which seemed to hold for both genders, for obesity-driven and non–obesity-driven cancers, and for patients with type 1 as well as type 2 diabetes – a new finding, according to Mr. Bendix Carstensen.

His large, population-based study found no overall excess risk of cancers among type 1 diabetes patients, compared with the general population.

“Based on this, we can exclude a major carcinogenic effect of exogenous insulin among those with type 1 diabetes, because if there was such an effect we would see some substantial increases in at least some cancers,” said Mr. Carstensen, an epidemiologist at the Steno Diabetes Center in Gentofte, Denmark.

Cancer and type 1 diabetes

The study examined cancer rates in patients with type 1 diabetes from five countries: Australia, Denmark, Finland, Scotland, and Sweden. Type 1 diabetes was defined as a diabetes diagnosis that occurred before age 30. In general, these registries contained patients who were still younger than 60 years. Despite the very large 4.6 million person-years of follow-up, the databases represent a population that does not exhibit the typical age-related increase in cancer risk – a slight limitation of the study, Mr. Carstensen noted.

The databases identified 9,369 cases of cancer among patients with type 1 diabetes. They were classified by gender, age, date of cancer diagnosis, and cancer rate, compared with that of the country’s entire population stratified by the same variables.

The crude rate of cancers in all the diabetes patients combined was no different from that of the general populations, with a risk ratio of 1.00 for men and 1.04 for women.

When cancers were examined by site and gender, some significant differences did arise between the diabetic and nondiabetic groups. Stomach cancer was 19% more likely in men and 75% more likely in women. The risk of pancreatic cancer was 70% increased in men and 36% in women. The risk of liver cancer was about doubled in each gender, and for kidney cancer, the risk was 29% in men and 42% in women. For women, there was a 53% increase in the risk of endometrial cancer.

In the time-dependent analysis, Mr. Carstensen found that almost all of the cancers diagnoses were made in the first year after diabetes was diagnosed and dropped rapidly thereafter. The extended time curve showed no lasting impact of diabetes on overall cancer incidence.

A more specific analysis looked at the time-dependent rate ratios of prostate and colorectal cancers for men, and breast, endometrial, and colorectal cancers in women. Each curve showed the high rate ratio in the first few years, followed by a drop-off and no lasting impact.

There were also no lasting impacts of diabetes on lung cancer, melanoma, or non-Hodgkins lymphoma in either gender.

“We did see an elevated site-specific cancer pattern in patients with type 1 diabetes, but no overall excess,” he said. “For these patients, the total cancer occurrence is not really different from population rates.”

Detection bias in diabetes and obesity

Another large, population-based study came to a similar conclusion for those with type 2 diabetes. In fact, “Detection bias may be the main cause of the increased cancer incidence among patients with diabetes,” Dr. Kirstin De Bruijn said.

She presented a subanalysis of the ongoing Rotterdam Study. The Rotterdam Study, launched in 1990, is investigating determinants of disease in residents aged 55 years and older. It now comprises about 11,000 subjects. Dr. De Bruijn of Erasmus University, Rotterdam, the Netherlands, investigated the association of cancer and diabetes in 10,181 patients. Of these, 906 had an incident type 2 diabetes diagnosis, and 2,238 had an incident cancer diagnosis during the mean follow-up period of 11 years. She looked at the incidence of breast, prostate, pancreatic, lung, and colorectal cancers.

In the overall analysis, the risk of any cancer was 30% increased in the patients with diabetes. This risk was attenuated, but remained statistically significant, in the fully adjusted model (hazard ratio, 1.2). In a cancer-specific analysis, however, only the risk of pancreatic cancer was significantly elevated (HR, 3.6 in the adjusted model). The risk of prostate cancer was 30% lower than that of the general population, but that was not a significant finding, she added.

She then looked at a time-dependent model that split the follow-up period into epochs according to time since diabetes diagnosis (up to 3 months, 3 months to 5 years, and more than 5 years).

The overall risk of a cancer diagnosis was more than three times higher in the first 3 months. It remained significantly elevated, though less so, in the first 5 years (HR, 1.5), and then fell off.

When the individual cancers were considered, only pancreatic cancer was significantly more common among the diabetes patients, and was almost 29 times more likely to be diagnosed in the first 3 months. However, Dr. De Bruijn noted, it’s tough to tease out that particular relationship, since the obesity that accompanies type 2 diabetes can also drive the development of pancreatic cancer.

Ellena Badrick, a researcher at the University of Manchester (England), also examined the idea of detection bias in a population database, exploring the time-dependent relationships for obesity-related cancers, compared with those not related to obesity.

She found 10,315 patients who were diagnosed with type 2 diabetes from 1995 to 2010. These were compared with 20,630 controls chosen from the same period. Obesity-related cancers were considered to be breast, endometrial, ovarian, renal, esophageal, pancreatic, and gallbladder.

There were 1,349 cancers among the patients with diabetes, of which 323 were related to obesity. Among the controls, there were 3,218 cancers, of which 634 were obesity related.

She also split her follow-up period into epochs since diabetes diagnosis: up to 6 months, 6-12 months, 12-24 months, 24 months-5 years, and beyond. Cancer incidence was reported as cases per 1,000 person/epoch.

There was a much higher detection rate overall in the first 6 months after diagnosis – more than 100 cases per 1,000 person-epoch. After 6 months, this dropped to less than 20 cases per 1,000 person-epoch. The incidence did increase over the follow-up period, but she said that reflected the expected age-related pattern.

The same pattern emerged when looking at obesity- vs. non–obesity-related cancers. In the first 6 months, the incidence of obesity-related cancer hovered around 30 per 1,000 person-epoch. By 1 year this had dropped to near zero. For non–obesity-related cancers, the incidence rate was much higher in the first 6 months, at nearly 80 per person/epoch. But this also dropped to near zero by 1 year. Both incidence curves followed the same slow increase as the subjects aged.

Over the entire follow-up, 27% of all the obesity-related cancers and 73% of the non–obesity-related cancers were diagnosed within the first year after a diagnosis of type 2 diabetes.

When cancers diagnosed during the first 2 years were excluded, patients with type 2 diabetes had a 43% increase in the risk of developing an obesity-related cancer during the study. There was no increased risk, however, in developing a cancer not related to obesity.

“This suggests that in patients with type 2 diabetes, cancer risk-reduction strategies should be targeted against obesity-related cancers,” Ms. Badrick said.

Mr. Carstensen is an employee of the Steno Diabetes Center, which is owned by Novo Nordisk. He disclosed that he owns stock in the company. Dr. De Bruijn and Ms. Badrick had no financial disclosures.

VIENNA – Most of the increased risk of cancer associated with diabetes appears in the first year or so after diabetes diagnosis, suggesting that it’s mainly attributable to increased medical surveillance.

Three studies presented at the annual meeting of the European Association for the Study of Diabetes came to similar conclusions, which seemed to hold for both genders, for obesity-driven and non–obesity-driven cancers, and for patients with type 1 as well as type 2 diabetes – a new finding, according to Mr. Bendix Carstensen.

His large, population-based study found no overall excess risk of cancers among type 1 diabetes patients, compared with the general population.

“Based on this, we can exclude a major carcinogenic effect of exogenous insulin among those with type 1 diabetes, because if there was such an effect we would see some substantial increases in at least some cancers,” said Mr. Carstensen, an epidemiologist at the Steno Diabetes Center in Gentofte, Denmark.

Cancer and type 1 diabetes

The study examined cancer rates in patients with type 1 diabetes from five countries: Australia, Denmark, Finland, Scotland, and Sweden. Type 1 diabetes was defined as a diabetes diagnosis that occurred before age 30. In general, these registries contained patients who were still younger than 60 years. Despite the very large 4.6 million person-years of follow-up, the databases represent a population that does not exhibit the typical age-related increase in cancer risk – a slight limitation of the study, Mr. Carstensen noted.

The databases identified 9,369 cases of cancer among patients with type 1 diabetes. They were classified by gender, age, date of cancer diagnosis, and cancer rate, compared with that of the country’s entire population stratified by the same variables.

The crude rate of cancers in all the diabetes patients combined was no different from that of the general populations, with a risk ratio of 1.00 for men and 1.04 for women.

When cancers were examined by site and gender, some significant differences did arise between the diabetic and nondiabetic groups. Stomach cancer was 19% more likely in men and 75% more likely in women. The risk of pancreatic cancer was 70% increased in men and 36% in women. The risk of liver cancer was about doubled in each gender, and for kidney cancer, the risk was 29% in men and 42% in women. For women, there was a 53% increase in the risk of endometrial cancer.

In the time-dependent analysis, Mr. Carstensen found that almost all of the cancers diagnoses were made in the first year after diabetes was diagnosed and dropped rapidly thereafter. The extended time curve showed no lasting impact of diabetes on overall cancer incidence.

A more specific analysis looked at the time-dependent rate ratios of prostate and colorectal cancers for men, and breast, endometrial, and colorectal cancers in women. Each curve showed the high rate ratio in the first few years, followed by a drop-off and no lasting impact.

There were also no lasting impacts of diabetes on lung cancer, melanoma, or non-Hodgkins lymphoma in either gender.

“We did see an elevated site-specific cancer pattern in patients with type 1 diabetes, but no overall excess,” he said. “For these patients, the total cancer occurrence is not really different from population rates.”

Detection bias in diabetes and obesity

Another large, population-based study came to a similar conclusion for those with type 2 diabetes. In fact, “Detection bias may be the main cause of the increased cancer incidence among patients with diabetes,” Dr. Kirstin De Bruijn said.

She presented a subanalysis of the ongoing Rotterdam Study. The Rotterdam Study, launched in 1990, is investigating determinants of disease in residents aged 55 years and older. It now comprises about 11,000 subjects. Dr. De Bruijn of Erasmus University, Rotterdam, the Netherlands, investigated the association of cancer and diabetes in 10,181 patients. Of these, 906 had an incident type 2 diabetes diagnosis, and 2,238 had an incident cancer diagnosis during the mean follow-up period of 11 years. She looked at the incidence of breast, prostate, pancreatic, lung, and colorectal cancers.

In the overall analysis, the risk of any cancer was 30% increased in the patients with diabetes. This risk was attenuated, but remained statistically significant, in the fully adjusted model (hazard ratio, 1.2). In a cancer-specific analysis, however, only the risk of pancreatic cancer was significantly elevated (HR, 3.6 in the adjusted model). The risk of prostate cancer was 30% lower than that of the general population, but that was not a significant finding, she added.

She then looked at a time-dependent model that split the follow-up period into epochs according to time since diabetes diagnosis (up to 3 months, 3 months to 5 years, and more than 5 years).

The overall risk of a cancer diagnosis was more than three times higher in the first 3 months. It remained significantly elevated, though less so, in the first 5 years (HR, 1.5), and then fell off.

When the individual cancers were considered, only pancreatic cancer was significantly more common among the diabetes patients, and was almost 29 times more likely to be diagnosed in the first 3 months. However, Dr. De Bruijn noted, it’s tough to tease out that particular relationship, since the obesity that accompanies type 2 diabetes can also drive the development of pancreatic cancer.

Ellena Badrick, a researcher at the University of Manchester (England), also examined the idea of detection bias in a population database, exploring the time-dependent relationships for obesity-related cancers, compared with those not related to obesity.

She found 10,315 patients who were diagnosed with type 2 diabetes from 1995 to 2010. These were compared with 20,630 controls chosen from the same period. Obesity-related cancers were considered to be breast, endometrial, ovarian, renal, esophageal, pancreatic, and gallbladder.

There were 1,349 cancers among the patients with diabetes, of which 323 were related to obesity. Among the controls, there were 3,218 cancers, of which 634 were obesity related.

She also split her follow-up period into epochs since diabetes diagnosis: up to 6 months, 6-12 months, 12-24 months, 24 months-5 years, and beyond. Cancer incidence was reported as cases per 1,000 person/epoch.

There was a much higher detection rate overall in the first 6 months after diagnosis – more than 100 cases per 1,000 person-epoch. After 6 months, this dropped to less than 20 cases per 1,000 person-epoch. The incidence did increase over the follow-up period, but she said that reflected the expected age-related pattern.

The same pattern emerged when looking at obesity- vs. non–obesity-related cancers. In the first 6 months, the incidence of obesity-related cancer hovered around 30 per 1,000 person-epoch. By 1 year this had dropped to near zero. For non–obesity-related cancers, the incidence rate was much higher in the first 6 months, at nearly 80 per person/epoch. But this also dropped to near zero by 1 year. Both incidence curves followed the same slow increase as the subjects aged.

Over the entire follow-up, 27% of all the obesity-related cancers and 73% of the non–obesity-related cancers were diagnosed within the first year after a diagnosis of type 2 diabetes.

When cancers diagnosed during the first 2 years were excluded, patients with type 2 diabetes had a 43% increase in the risk of developing an obesity-related cancer during the study. There was no increased risk, however, in developing a cancer not related to obesity.

“This suggests that in patients with type 2 diabetes, cancer risk-reduction strategies should be targeted against obesity-related cancers,” Ms. Badrick said.

Mr. Carstensen is an employee of the Steno Diabetes Center, which is owned by Novo Nordisk. He disclosed that he owns stock in the company. Dr. De Bruijn and Ms. Badrick had no financial disclosures.

VIENNA – Most of the increased risk of cancer associated with diabetes appears in the first year or so after diabetes diagnosis, suggesting that it’s mainly attributable to increased medical surveillance.

Three studies presented at the annual meeting of the European Association for the Study of Diabetes came to similar conclusions, which seemed to hold for both genders, for obesity-driven and non–obesity-driven cancers, and for patients with type 1 as well as type 2 diabetes – a new finding, according to Mr. Bendix Carstensen.

His large, population-based study found no overall excess risk of cancers among type 1 diabetes patients, compared with the general population.

“Based on this, we can exclude a major carcinogenic effect of exogenous insulin among those with type 1 diabetes, because if there was such an effect we would see some substantial increases in at least some cancers,” said Mr. Carstensen, an epidemiologist at the Steno Diabetes Center in Gentofte, Denmark.

Cancer and type 1 diabetes

The study examined cancer rates in patients with type 1 diabetes from five countries: Australia, Denmark, Finland, Scotland, and Sweden. Type 1 diabetes was defined as a diabetes diagnosis that occurred before age 30. In general, these registries contained patients who were still younger than 60 years. Despite the very large 4.6 million person-years of follow-up, the databases represent a population that does not exhibit the typical age-related increase in cancer risk – a slight limitation of the study, Mr. Carstensen noted.

The databases identified 9,369 cases of cancer among patients with type 1 diabetes. They were classified by gender, age, date of cancer diagnosis, and cancer rate, compared with that of the country’s entire population stratified by the same variables.

The crude rate of cancers in all the diabetes patients combined was no different from that of the general populations, with a risk ratio of 1.00 for men and 1.04 for women.

When cancers were examined by site and gender, some significant differences did arise between the diabetic and nondiabetic groups. Stomach cancer was 19% more likely in men and 75% more likely in women. The risk of pancreatic cancer was 70% increased in men and 36% in women. The risk of liver cancer was about doubled in each gender, and for kidney cancer, the risk was 29% in men and 42% in women. For women, there was a 53% increase in the risk of endometrial cancer.

In the time-dependent analysis, Mr. Carstensen found that almost all of the cancers diagnoses were made in the first year after diabetes was diagnosed and dropped rapidly thereafter. The extended time curve showed no lasting impact of diabetes on overall cancer incidence.

A more specific analysis looked at the time-dependent rate ratios of prostate and colorectal cancers for men, and breast, endometrial, and colorectal cancers in women. Each curve showed the high rate ratio in the first few years, followed by a drop-off and no lasting impact.

There were also no lasting impacts of diabetes on lung cancer, melanoma, or non-Hodgkins lymphoma in either gender.

“We did see an elevated site-specific cancer pattern in patients with type 1 diabetes, but no overall excess,” he said. “For these patients, the total cancer occurrence is not really different from population rates.”

Detection bias in diabetes and obesity

Another large, population-based study came to a similar conclusion for those with type 2 diabetes. In fact, “Detection bias may be the main cause of the increased cancer incidence among patients with diabetes,” Dr. Kirstin De Bruijn said.

She presented a subanalysis of the ongoing Rotterdam Study. The Rotterdam Study, launched in 1990, is investigating determinants of disease in residents aged 55 years and older. It now comprises about 11,000 subjects. Dr. De Bruijn of Erasmus University, Rotterdam, the Netherlands, investigated the association of cancer and diabetes in 10,181 patients. Of these, 906 had an incident type 2 diabetes diagnosis, and 2,238 had an incident cancer diagnosis during the mean follow-up period of 11 years. She looked at the incidence of breast, prostate, pancreatic, lung, and colorectal cancers.

In the overall analysis, the risk of any cancer was 30% increased in the patients with diabetes. This risk was attenuated, but remained statistically significant, in the fully adjusted model (hazard ratio, 1.2). In a cancer-specific analysis, however, only the risk of pancreatic cancer was significantly elevated (HR, 3.6 in the adjusted model). The risk of prostate cancer was 30% lower than that of the general population, but that was not a significant finding, she added.

She then looked at a time-dependent model that split the follow-up period into epochs according to time since diabetes diagnosis (up to 3 months, 3 months to 5 years, and more than 5 years).

The overall risk of a cancer diagnosis was more than three times higher in the first 3 months. It remained significantly elevated, though less so, in the first 5 years (HR, 1.5), and then fell off.

When the individual cancers were considered, only pancreatic cancer was significantly more common among the diabetes patients, and was almost 29 times more likely to be diagnosed in the first 3 months. However, Dr. De Bruijn noted, it’s tough to tease out that particular relationship, since the obesity that accompanies type 2 diabetes can also drive the development of pancreatic cancer.

Ellena Badrick, a researcher at the University of Manchester (England), also examined the idea of detection bias in a population database, exploring the time-dependent relationships for obesity-related cancers, compared with those not related to obesity.

She found 10,315 patients who were diagnosed with type 2 diabetes from 1995 to 2010. These were compared with 20,630 controls chosen from the same period. Obesity-related cancers were considered to be breast, endometrial, ovarian, renal, esophageal, pancreatic, and gallbladder.

There were 1,349 cancers among the patients with diabetes, of which 323 were related to obesity. Among the controls, there were 3,218 cancers, of which 634 were obesity related.

She also split her follow-up period into epochs since diabetes diagnosis: up to 6 months, 6-12 months, 12-24 months, 24 months-5 years, and beyond. Cancer incidence was reported as cases per 1,000 person/epoch.

There was a much higher detection rate overall in the first 6 months after diagnosis – more than 100 cases per 1,000 person-epoch. After 6 months, this dropped to less than 20 cases per 1,000 person-epoch. The incidence did increase over the follow-up period, but she said that reflected the expected age-related pattern.

The same pattern emerged when looking at obesity- vs. non–obesity-related cancers. In the first 6 months, the incidence of obesity-related cancer hovered around 30 per 1,000 person-epoch. By 1 year this had dropped to near zero. For non–obesity-related cancers, the incidence rate was much higher in the first 6 months, at nearly 80 per person/epoch. But this also dropped to near zero by 1 year. Both incidence curves followed the same slow increase as the subjects aged.

Over the entire follow-up, 27% of all the obesity-related cancers and 73% of the non–obesity-related cancers were diagnosed within the first year after a diagnosis of type 2 diabetes.

When cancers diagnosed during the first 2 years were excluded, patients with type 2 diabetes had a 43% increase in the risk of developing an obesity-related cancer during the study. There was no increased risk, however, in developing a cancer not related to obesity.

“This suggests that in patients with type 2 diabetes, cancer risk-reduction strategies should be targeted against obesity-related cancers,” Ms. Badrick said.

Mr. Carstensen is an employee of the Steno Diabetes Center, which is owned by Novo Nordisk. He disclosed that he owns stock in the company. Dr. De Bruijn and Ms. Badrick had no financial disclosures.

VIENNA – Most of the increased risk of cancer associated with diabetes appears in the first year or so after diabetes diagnosis, suggesting that it’s mainly attributable to increased medical surveillance.

Three studies presented at the annual meeting of the European Association for the Study of Diabetes came to similar conclusions, which seemed to hold for both genders, for obesity-driven and non–obesity-driven cancers, and for patients with type 1 as well as type 2 diabetes – a new finding, according to Mr. Bendix Carstensen.

His large, population-based study found no overall excess risk of cancers among type 1 diabetes patients, compared with the general population.

“Based on this, we can exclude a major carcinogenic effect of exogenous insulin among those with type 1 diabetes, because if there was such an effect we would see some substantial increases in at least some cancers,” said Mr. Carstensen, an epidemiologist at the Steno Diabetes Center in Gentofte, Denmark.

Cancer and type 1 diabetes

The study examined cancer rates in patients with type 1 diabetes from five countries: Australia, Denmark, Finland, Scotland, and Sweden. Type 1 diabetes was defined as a diabetes diagnosis that occurred before age 30. In general, these registries contained patients who were still younger than 60 years. Despite the very large 4.6 million person-years of follow-up, the databases represent a population that does not exhibit the typical age-related increase in cancer risk – a slight limitation of the study, Mr. Carstensen noted.

The databases identified 9,369 cases of cancer among patients with type 1 diabetes. They were classified by gender, age, date of cancer diagnosis, and cancer rate, compared with that of the country’s entire population stratified by the same variables.

The crude rate of cancers in all the diabetes patients combined was no different from that of the general populations, with a risk ratio of 1.00 for men and 1.04 for women.

When cancers were examined by site and gender, some significant differences did arise between the diabetic and nondiabetic groups. Stomach cancer was 19% more likely in men and 75% more likely in women. The risk of pancreatic cancer was 70% increased in men and 36% in women. The risk of liver cancer was about doubled in each gender, and for kidney cancer, the risk was 29% in men and 42% in women. For women, there was a 53% increase in the risk of endometrial cancer.

In the time-dependent analysis, Mr. Carstensen found that almost all of the cancers diagnoses were made in the first year after diabetes was diagnosed and dropped rapidly thereafter. The extended time curve showed no lasting impact of diabetes on overall cancer incidence.

A more specific analysis looked at the time-dependent rate ratios of prostate and colorectal cancers for men, and breast, endometrial, and colorectal cancers in women. Each curve showed the high rate ratio in the first few years, followed by a drop-off and no lasting impact.

There were also no lasting impacts of diabetes on lung cancer, melanoma, or non-Hodgkins lymphoma in either gender.

“We did see an elevated site-specific cancer pattern in patients with type 1 diabetes, but no overall excess,” he said. “For these patients, the total cancer occurrence is not really different from population rates.”

Detection bias in diabetes and obesity

Another large, population-based study came to a similar conclusion for those with type 2 diabetes. In fact, “Detection bias may be the main cause of the increased cancer incidence among patients with diabetes,” Dr. Kirstin De Bruijn said.

She presented a subanalysis of the ongoing Rotterdam Study. The Rotterdam Study, launched in 1990, is investigating determinants of disease in residents aged 55 years and older. It now comprises about 11,000 subjects. Dr. De Bruijn of Erasmus University, Rotterdam, the Netherlands, investigated the association of cancer and diabetes in 10,181 patients. Of these, 906 had an incident type 2 diabetes diagnosis, and 2,238 had an incident cancer diagnosis during the mean follow-up period of 11 years. She looked at the incidence of breast, prostate, pancreatic, lung, and colorectal cancers.

In the overall analysis, the risk of any cancer was 30% increased in the patients with diabetes. This risk was attenuated, but remained statistically significant, in the fully adjusted model (hazard ratio, 1.2). In a cancer-specific analysis, however, only the risk of pancreatic cancer was significantly elevated (HR, 3.6 in the adjusted model). The risk of prostate cancer was 30% lower than that of the general population, but that was not a significant finding, she added.

She then looked at a time-dependent model that split the follow-up period into epochs according to time since diabetes diagnosis (up to 3 months, 3 months to 5 years, and more than 5 years).

The overall risk of a cancer diagnosis was more than three times higher in the first 3 months. It remained significantly elevated, though less so, in the first 5 years (HR, 1.5), and then fell off.

When the individual cancers were considered, only pancreatic cancer was significantly more common among the diabetes patients, and was almost 29 times more likely to be diagnosed in the first 3 months. However, Dr. De Bruijn noted, it’s tough to tease out that particular relationship, since the obesity that accompanies type 2 diabetes can also drive the development of pancreatic cancer.

Ellena Badrick, a researcher at the University of Manchester (England), also examined the idea of detection bias in a population database, exploring the time-dependent relationships for obesity-related cancers, compared with those not related to obesity.

She found 10,315 patients who were diagnosed with type 2 diabetes from 1995 to 2010. These were compared with 20,630 controls chosen from the same period. Obesity-related cancers were considered to be breast, endometrial, ovarian, renal, esophageal, pancreatic, and gallbladder.

There were 1,349 cancers among the patients with diabetes, of which 323 were related to obesity. Among the controls, there were 3,218 cancers, of which 634 were obesity related.

She also split her follow-up period into epochs since diabetes diagnosis: up to 6 months, 6-12 months, 12-24 months, 24 months-5 years, and beyond. Cancer incidence was reported as cases per 1,000 person/epoch.

There was a much higher detection rate overall in the first 6 months after diagnosis – more than 100 cases per 1,000 person-epoch. After 6 months, this dropped to less than 20 cases per 1,000 person-epoch. The incidence did increase over the follow-up period, but she said that reflected the expected age-related pattern.

The same pattern emerged when looking at obesity- vs. non–obesity-related cancers. In the first 6 months, the incidence of obesity-related cancer hovered around 30 per 1,000 person-epoch. By 1 year this had dropped to near zero. For non–obesity-related cancers, the incidence rate was much higher in the first 6 months, at nearly 80 per person/epoch. But this also dropped to near zero by 1 year. Both incidence curves followed the same slow increase as the subjects aged.

Over the entire follow-up, 27% of all the obesity-related cancers and 73% of the non–obesity-related cancers were diagnosed within the first year after a diagnosis of type 2 diabetes.

When cancers diagnosed during the first 2 years were excluded, patients with type 2 diabetes had a 43% increase in the risk of developing an obesity-related cancer during the study. There was no increased risk, however, in developing a cancer not related to obesity.

“This suggests that in patients with type 2 diabetes, cancer risk-reduction strategies should be targeted against obesity-related cancers,” Ms. Badrick said.

Mr. Carstensen is an employee of the Steno Diabetes Center, which is owned by Novo Nordisk. He disclosed that he owns stock in the company. Dr. De Bruijn and Ms. Badrick had no financial disclosures.

[email protected]

On Twitter @alz_gal

VIENNA – Most of the increased risk of cancer associated with diabetes appears in the first year or so after diabetes diagnosis, suggesting that it’s mainly attributable to increased medical surveillance.

Three studies presented at the annual meeting of the European Association for the Study of Diabetes came to similar conclusions, which seemed to hold for both genders, for obesity-driven and non–obesity-driven cancers, and for patients with type 1 as well as type 2 diabetes – a new finding, according to Mr. Bendix Carstensen.

His large, population-based study found no overall excess risk of cancers among type 1 diabetes patients, compared with the general population.

“Based on this, we can exclude a major carcinogenic effect of exogenous insulin among those with type 1 diabetes, because if there was such an effect we would see some substantial increases in at least some cancers,” said Mr. Carstensen, an epidemiologist at the Steno Diabetes Center in Gentofte, Denmark.

Cancer and type 1 diabetes

The study examined cancer rates in patients with type 1 diabetes from five countries: Australia, Denmark, Finland, Scotland, and Sweden. Type 1 diabetes was defined as a diabetes diagnosis that occurred before age 30. In general, these registries contained patients who were still younger than 60 years. Despite the very large 4.6 million person-years of follow-up, the databases represent a population that does not exhibit the typical age-related increase in cancer risk – a slight limitation of the study, Mr. Carstensen noted.

The databases identified 9,369 cases of cancer among patients with type 1 diabetes. They were classified by gender, age, date of cancer diagnosis, and cancer rate, compared with that of the country’s entire population stratified by the same variables.

The crude rate of cancers in all the diabetes patients combined was no different from that of the general populations, with a risk ratio of 1.00 for men and 1.04 for women.

When cancers were examined by site and gender, some significant differences did arise between the diabetic and nondiabetic groups. Stomach cancer was 19% more likely in men and 75% more likely in women. The risk of pancreatic cancer was 70% increased in men and 36% in women. The risk of liver cancer was about doubled in each gender, and for kidney cancer, the risk was 29% in men and 42% in women. For women, there was a 53% increase in the risk of endometrial cancer.

In the time-dependent analysis, Mr. Carstensen found that almost all of the cancers diagnoses were made in the first year after diabetes was diagnosed and dropped rapidly thereafter. The extended time curve showed no lasting impact of diabetes on overall cancer incidence.

A more specific analysis looked at the time-dependent rate ratios of prostate and colorectal cancers for men, and breast, endometrial, and colorectal cancers in women. Each curve showed the high rate ratio in the first few years, followed by a drop-off and no lasting impact.

There were also no lasting impacts of diabetes on lung cancer, melanoma, or non-Hodgkins lymphoma in either gender.

“We did see an elevated site-specific cancer pattern in patients with type 1 diabetes, but no overall excess,” he said. “For these patients, the total cancer occurrence is not really different from population rates.”

Detection bias in diabetes and obesity

Another large, population-based study came to a similar conclusion for those with type 2 diabetes. In fact, “Detection bias may be the main cause of the increased cancer incidence among patients with diabetes,” Dr. Kirstin De Bruijn said.

She presented a subanalysis of the ongoing Rotterdam Study. The Rotterdam Study, launched in 1990, is investigating determinants of disease in residents aged 55 years and older. It now comprises about 11,000 subjects. Dr. De Bruijn of Erasmus University, Rotterdam, the Netherlands, investigated the association of cancer and diabetes in 10,181 patients. Of these, 906 had an incident type 2 diabetes diagnosis, and 2,238 had an incident cancer diagnosis during the mean follow-up period of 11 years. She looked at the incidence of breast, prostate, pancreatic, lung, and colorectal cancers.

In the overall analysis, the risk of any cancer was 30% increased in the patients with diabetes. This risk was attenuated, but remained statistically significant, in the fully adjusted model (hazard ratio, 1.2). In a cancer-specific analysis, however, only the risk of pancreatic cancer was significantly elevated (HR, 3.6 in the adjusted model). The risk of prostate cancer was 30% lower than that of the general population, but that was not a significant finding, she added.

She then looked at a time-dependent model that split the follow-up period into epochs according to time since diabetes diagnosis (up to 3 months, 3 months to 5 years, and more than 5 years).

The overall risk of a cancer diagnosis was more than three times higher in the first 3 months. It remained significantly elevated, though less so, in the first 5 years (HR, 1.5), and then fell off.

When the individual cancers were considered, only pancreatic cancer was significantly more common among the diabetes patients, and was almost 29 times more likely to be diagnosed in the first 3 months. However, Dr. De Bruijn noted, it’s tough to tease out that particular relationship, since the obesity that accompanies type 2 diabetes can also drive the development of pancreatic cancer.

Ellena Badrick, a researcher at the University of Manchester (England), also examined the idea of detection bias in a population database, exploring the time-dependent relationships for obesity-related cancers, compared with those not related to obesity.

She found 10,315 patients who were diagnosed with type 2 diabetes from 1995 to 2010. These were compared with 20,630 controls chosen from the same period. Obesity-related cancers were considered to be breast, endometrial, ovarian, renal, esophageal, pancreatic, and gallbladder.

There were 1,349 cancers among the patients with diabetes, of which 323 were related to obesity. Among the controls, there were 3,218 cancers, of which 634 were obesity related.

She also split her follow-up period into epochs since diabetes diagnosis: up to 6 months, 6-12 months, 12-24 months, 24 months-5 years, and beyond. Cancer incidence was reported as cases per 1,000 person/epoch.

There was a much higher detection rate overall in the first 6 months after diagnosis – more than 100 cases per 1,000 person-epoch. After 6 months, this dropped to less than 20 cases per 1,000 person-epoch. The incidence did increase over the follow-up period, but she said that reflected the expected age-related pattern.

The same pattern emerged when looking at obesity- vs. non–obesity-related cancers. In the first 6 months, the incidence of obesity-related cancer hovered around 30 per 1,000 person-epoch. By 1 year this had dropped to near zero. For non–obesity-related cancers, the incidence rate was much higher in the first 6 months, at nearly 80 per person/epoch. But this also dropped to near zero by 1 year. Both incidence curves followed the same slow increase as the subjects aged.

Over the entire follow-up, 27% of all the obesity-related cancers and 73% of the non–obesity-related cancers were diagnosed within the first year after a diagnosis of type 2 diabetes.

When cancers diagnosed during the first 2 years were excluded, patients with type 2 diabetes had a 43% increase in the risk of developing an obesity-related cancer during the study. There was no increased risk, however, in developing a cancer not related to obesity.

“This suggests that in patients with type 2 diabetes, cancer risk-reduction strategies should be targeted against obesity-related cancers,” Ms. Badrick said.

Mr. Carstensen is an employee of the Steno Diabetes Center, which is owned by Novo Nordisk. He disclosed that he owns stock in the company. Dr. De Bruijn and Ms. Badrick had no financial disclosures.

[email protected]

On Twitter @alz_gal

VIENNA – Most of the increased risk of cancer associated with diabetes appears in the first year or so after diabetes diagnosis, suggesting that it’s mainly attributable to increased medical surveillance.

Three studies presented at the annual meeting of the European Association for the Study of Diabetes came to similar conclusions, which seemed to hold for both genders, for obesity-driven and non–obesity-driven cancers, and for patients with type 1 as well as type 2 diabetes – a new finding, according to Mr. Bendix Carstensen.

His large, population-based study found no overall excess risk of cancers among type 1 diabetes patients, compared with the general population.

“Based on this, we can exclude a major carcinogenic effect of exogenous insulin among those with type 1 diabetes, because if there was such an effect we would see some substantial increases in at least some cancers,” said Mr. Carstensen, an epidemiologist at the Steno Diabetes Center in Gentofte, Denmark.

Cancer and type 1 diabetes

The study examined cancer rates in patients with type 1 diabetes from five countries: Australia, Denmark, Finland, Scotland, and Sweden. Type 1 diabetes was defined as a diabetes diagnosis that occurred before age 30. In general, these registries contained patients who were still younger than 60 years. Despite the very large 4.6 million person-years of follow-up, the databases represent a population that does not exhibit the typical age-related increase in cancer risk – a slight limitation of the study, Mr. Carstensen noted.

The databases identified 9,369 cases of cancer among patients with type 1 diabetes. They were classified by gender, age, date of cancer diagnosis, and cancer rate, compared with that of the country’s entire population stratified by the same variables.

The crude rate of cancers in all the diabetes patients combined was no different from that of the general populations, with a risk ratio of 1.00 for men and 1.04 for women.

When cancers were examined by site and gender, some significant differences did arise between the diabetic and nondiabetic groups. Stomach cancer was 19% more likely in men and 75% more likely in women. The risk of pancreatic cancer was 70% increased in men and 36% in women. The risk of liver cancer was about doubled in each gender, and for kidney cancer, the risk was 29% in men and 42% in women. For women, there was a 53% increase in the risk of endometrial cancer.

In the time-dependent analysis, Mr. Carstensen found that almost all of the cancers diagnoses were made in the first year after diabetes was diagnosed and dropped rapidly thereafter. The extended time curve showed no lasting impact of diabetes on overall cancer incidence.

A more specific analysis looked at the time-dependent rate ratios of prostate and colorectal cancers for men, and breast, endometrial, and colorectal cancers in women. Each curve showed the high rate ratio in the first few years, followed by a drop-off and no lasting impact.

There were also no lasting impacts of diabetes on lung cancer, melanoma, or non-Hodgkins lymphoma in either gender.

“We did see an elevated site-specific cancer pattern in patients with type 1 diabetes, but no overall excess,” he said. “For these patients, the total cancer occurrence is not really different from population rates.”

Detection bias in diabetes and obesity

Another large, population-based study came to a similar conclusion for those with type 2 diabetes. In fact, “Detection bias may be the main cause of the increased cancer incidence among patients with diabetes,” Dr. Kirstin De Bruijn said.

She presented a subanalysis of the ongoing Rotterdam Study. The Rotterdam Study, launched in 1990, is investigating determinants of disease in residents aged 55 years and older. It now comprises about 11,000 subjects. Dr. De Bruijn of Erasmus University, Rotterdam, the Netherlands, investigated the association of cancer and diabetes in 10,181 patients. Of these, 906 had an incident type 2 diabetes diagnosis, and 2,238 had an incident cancer diagnosis during the mean follow-up period of 11 years. She looked at the incidence of breast, prostate, pancreatic, lung, and colorectal cancers.

In the overall analysis, the risk of any cancer was 30% increased in the patients with diabetes. This risk was attenuated, but remained statistically significant, in the fully adjusted model (hazard ratio, 1.2). In a cancer-specific analysis, however, only the risk of pancreatic cancer was significantly elevated (HR, 3.6 in the adjusted model). The risk of prostate cancer was 30% lower than that of the general population, but that was not a significant finding, she added.

She then looked at a time-dependent model that split the follow-up period into epochs according to time since diabetes diagnosis (up to 3 months, 3 months to 5 years, and more than 5 years).

The overall risk of a cancer diagnosis was more than three times higher in the first 3 months. It remained significantly elevated, though less so, in the first 5 years (HR, 1.5), and then fell off.

When the individual cancers were considered, only pancreatic cancer was significantly more common among the diabetes patients, and was almost 29 times more likely to be diagnosed in the first 3 months. However, Dr. De Bruijn noted, it’s tough to tease out that particular relationship, since the obesity that accompanies type 2 diabetes can also drive the development of pancreatic cancer.

Ellena Badrick, a researcher at the University of Manchester (England), also examined the idea of detection bias in a population database, exploring the time-dependent relationships for obesity-related cancers, compared with those not related to obesity.

She found 10,315 patients who were diagnosed with type 2 diabetes from 1995 to 2010. These were compared with 20,630 controls chosen from the same period. Obesity-related cancers were considered to be breast, endometrial, ovarian, renal, esophageal, pancreatic, and gallbladder.

There were 1,349 cancers among the patients with diabetes, of which 323 were related to obesity. Among the controls, there were 3,218 cancers, of which 634 were obesity related.

She also split her follow-up period into epochs since diabetes diagnosis: up to 6 months, 6-12 months, 12-24 months, 24 months-5 years, and beyond. Cancer incidence was reported as cases per 1,000 person/epoch.

There was a much higher detection rate overall in the first 6 months after diagnosis – more than 100 cases per 1,000 person-epoch. After 6 months, this dropped to less than 20 cases per 1,000 person-epoch. The incidence did increase over the follow-up period, but she said that reflected the expected age-related pattern.

The same pattern emerged when looking at obesity- vs. non–obesity-related cancers. In the first 6 months, the incidence of obesity-related cancer hovered around 30 per 1,000 person-epoch. By 1 year this had dropped to near zero. For non–obesity-related cancers, the incidence rate was much higher in the first 6 months, at nearly 80 per person/epoch. But this also dropped to near zero by 1 year. Both incidence curves followed the same slow increase as the subjects aged.

Over the entire follow-up, 27% of all the obesity-related cancers and 73% of the non–obesity-related cancers were diagnosed within the first year after a diagnosis of type 2 diabetes.

When cancers diagnosed during the first 2 years were excluded, patients with type 2 diabetes had a 43% increase in the risk of developing an obesity-related cancer during the study. There was no increased risk, however, in developing a cancer not related to obesity.

“This suggests that in patients with type 2 diabetes, cancer risk-reduction strategies should be targeted against obesity-related cancers,” Ms. Badrick said.

Mr. Carstensen is an employee of the Steno Diabetes Center, which is owned by Novo Nordisk. He disclosed that he owns stock in the company. Dr. De Bruijn and Ms. Badrick had no financial disclosures.

[email protected]

On Twitter @alz_gal

VIENNA – A hemoglobin A_1c of less than 7% was achieved by 78% patients with type 2 diabetes when insulin degludec (IDeg) was added to oral antidiabetic drug therapy in a randomized, double blind, phase III study.

In comparison, 36% of patients treated with the glucagon-like peptide 1 (GLP-1) agonist liraglutide (Victoza, Novo Nordisk) on top of metformin achieved this blood glucose target, with an odds ratio favoring treatment intensification of 7.79.

Furthermore, after about 6 months of treatment, HbA_1c was 0.92% lower in the insulin-added arm than in the control arm, with mean end-of-treatment values of 6.5% versus 7.5% (P < .0001), respectively.

“This treatment approach also resulted in lower fasting plasma glucose [FPG] … and overall low rates of hypoglycemia,” Dr. Vanita Aroda of MedStar Health Research Institute in Hyattsville, Md., said at the annual meeting of the European Association for the Study of Diabetes.

IDeg (Tresiba, Novo Nordisk) is an ultra-long-acting basal insulin analogue currently approved for use in Europe and some other countries around the world. A dual, once-daily, single-injection formulation of IDeg and liraglutide (Xultophy, Novo Nordisk) also is under investigation.

Results from the DUAL (Dual Action of Liraglutide and Insulin Degludec in Type 2 Diabetes) program with the fixed dose combination were reported elsewhere at the EASD annual meeting and recently reported (Lancet Diabetes Endocrinol. 2014 Sept. 2 [doi:10.1016/S2213-8587(14)70174-3]).

In the present study, Dr. Aroda and her associates aimed to confirm the efficacy and safety of IDeg given separately but in combination with liraglutide and metformin versus these oral antidiabetic drugs (OADs) plus an injected insulin placebo.

A total of 1,504 patients with diabetes of at least 6 months’ duration, being treated with metformin or other OADs but not insulin, and in need of treatment intensification were screen for possible inclusion in the trial.

After a 15-week run-in period, during which time the dose of liraglutide was titrated up to 1.5 mg, 346 patients were randomized to receive liraglutide plus metformin and either IDeg or an injectable placebo.

Ninety-two percent of the 174 patients randomized to IDeg plus liraglutide and metformin completed the 26-week trial, as did 76% of the 172 randomized to the placebo arm. Baseline characteristics of the two groups of patients were similar, with a mean age of 57 years, 9 years’ diabetes duration, and a starting HbA_1c of about 7.5%.

FPG values at baseline were 8.7 mmol/L in the intensified arm and 9.1 mmol/L in the placebo arm. These decreased to 8.8 and 6.1 mmol/L, respectively, with an end-of-treatment difference of –2.55 mmol/L favoring the intensified arm, a highly significant difference.

Daily insulin doses at the end of treatment were 51 units in the intensified arm and the equivalent of 105 units in the placebo arm.

Mean body weight was lower in the IDeg-supplemented arm than in the placebo arm at baseline (90.7 kg vs. 94.2 kg), and there was an average weight gain of 2 kg and weight loss of 1.3 kg in each arm, respectively, over the study period, such that the mean body weight at the end of the trial was the same, at 92.7 kg.

No cases of severe hypoglycemia were reported, and there was no significant difference in the number of confirmed nocturnal hypoglycemia cases (four events in three patients with IDeg versus two events in two patients with placebo). The rate of confirmed hypoglycemia was significantly higher in insulin-treated patients (17.3% vs 4.7%); otherwise, both regimens studied were well tolerated.

Dr. Julio Rosenstock of Dallas Diabetes & Endocrine Center, who chaired the session, said that these results were “impressive” and that the study was much better designed than was a similar study with insulin detemir (Levemir, Novo Nordisk) added to liraglutide.

“This is better because you have a control injectable,” he said. “In the previous study with detemir the A_1c came down to 7.1% after 6 months, as reported by DeVries [Diabetes Care 2012;35:1446-54], and to 7.2%, as we reported, after 1 year [J. Diabetes Complications 2013;27:492-500].

“In that previous study the dose of detemir was 39 units, here it was 51 units, so the question is, are the better results because of a higher insulin dose, or because of a difference in the insulin?”

Dr. Rosenstock suggested that a head-to-head trial of insulin detemir and IDeg would be needed to determine the answer. Dr. Aroda agreed.

Dr. Aroda and Dr. Rosenstock disclosed ties with Novo Nordisk, which funded the study, and with other companies that manufacture diabetes medications and devices.

VIENNA – A hemoglobin A_1c of less than 7% was achieved by 78% patients with type 2 diabetes when insulin degludec (IDeg) was added to oral antidiabetic drug therapy in a randomized, double blind, phase III study.

In comparison, 36% of patients treated with the glucagon-like peptide 1 (GLP-1) agonist liraglutide (Victoza, Novo Nordisk) on top of metformin achieved this blood glucose target, with an odds ratio favoring treatment intensification of 7.79.

Furthermore, after about 6 months of treatment, HbA_1c was 0.92% lower in the insulin-added arm than in the control arm, with mean end-of-treatment values of 6.5% versus 7.5% (P < .0001), respectively.

“This treatment approach also resulted in lower fasting plasma glucose [FPG] … and overall low rates of hypoglycemia,” Dr. Vanita Aroda of MedStar Health Research Institute in Hyattsville, Md., said at the annual meeting of the European Association for the Study of Diabetes.

IDeg (Tresiba, Novo Nordisk) is an ultra-long-acting basal insulin analogue currently approved for use in Europe and some other countries around the world. A dual, once-daily, single-injection formulation of IDeg and liraglutide (Xultophy, Novo Nordisk) also is under investigation.

Results from the DUAL (Dual Action of Liraglutide and Insulin Degludec in Type 2 Diabetes) program with the fixed dose combination were reported elsewhere at the EASD annual meeting and recently reported (Lancet Diabetes Endocrinol. 2014 Sept. 2 [doi:10.1016/S2213-8587(14)70174-3]).

In the present study, Dr. Aroda and her associates aimed to confirm the efficacy and safety of IDeg given separately but in combination with liraglutide and metformin versus these oral antidiabetic drugs (OADs) plus an injected insulin placebo.

A total of 1,504 patients with diabetes of at least 6 months’ duration, being treated with metformin or other OADs but not insulin, and in need of treatment intensification were screen for possible inclusion in the trial.

After a 15-week run-in period, during which time the dose of liraglutide was titrated up to 1.5 mg, 346 patients were randomized to receive liraglutide plus metformin and either IDeg or an injectable placebo.

Ninety-two percent of the 174 patients randomized to IDeg plus liraglutide and metformin completed the 26-week trial, as did 76% of the 172 randomized to the placebo arm. Baseline characteristics of the two groups of patients were similar, with a mean age of 57 years, 9 years’ diabetes duration, and a starting HbA_1c of about 7.5%.

FPG values at baseline were 8.7 mmol/L in the intensified arm and 9.1 mmol/L in the placebo arm. These decreased to 8.8 and 6.1 mmol/L, respectively, with an end-of-treatment difference of –2.55 mmol/L favoring the intensified arm, a highly significant difference.

Daily insulin doses at the end of treatment were 51 units in the intensified arm and the equivalent of 105 units in the placebo arm.

Mean body weight was lower in the IDeg-supplemented arm than in the placebo arm at baseline (90.7 kg vs. 94.2 kg), and there was an average weight gain of 2 kg and weight loss of 1.3 kg in each arm, respectively, over the study period, such that the mean body weight at the end of the trial was the same, at 92.7 kg.

No cases of severe hypoglycemia were reported, and there was no significant difference in the number of confirmed nocturnal hypoglycemia cases (four events in three patients with IDeg versus two events in two patients with placebo). The rate of confirmed hypoglycemia was significantly higher in insulin-treated patients (17.3% vs 4.7%); otherwise, both regimens studied were well tolerated.

Dr. Julio Rosenstock of Dallas Diabetes & Endocrine Center, who chaired the session, said that these results were “impressive” and that the study was much better designed than was a similar study with insulin detemir (Levemir, Novo Nordisk) added to liraglutide.

“This is better because you have a control injectable,” he said. “In the previous study with detemir the A_1c came down to 7.1% after 6 months, as reported by DeVries [Diabetes Care 2012;35:1446-54], and to 7.2%, as we reported, after 1 year [J. Diabetes Complications 2013;27:492-500].

“In that previous study the dose of detemir was 39 units, here it was 51 units, so the question is, are the better results because of a higher insulin dose, or because of a difference in the insulin?”

Dr. Rosenstock suggested that a head-to-head trial of insulin detemir and IDeg would be needed to determine the answer. Dr. Aroda agreed.

Dr. Aroda and Dr. Rosenstock disclosed ties with Novo Nordisk, which funded the study, and with other companies that manufacture diabetes medications and devices.

VIENNA – A hemoglobin A_1c of less than 7% was achieved by 78% patients with type 2 diabetes when insulin degludec (IDeg) was added to oral antidiabetic drug therapy in a randomized, double blind, phase III study.

In comparison, 36% of patients treated with the glucagon-like peptide 1 (GLP-1) agonist liraglutide (Victoza, Novo Nordisk) on top of metformin achieved this blood glucose target, with an odds ratio favoring treatment intensification of 7.79.

Furthermore, after about 6 months of treatment, HbA_1c was 0.92% lower in the insulin-added arm than in the control arm, with mean end-of-treatment values of 6.5% versus 7.5% (P < .0001), respectively.

“This treatment approach also resulted in lower fasting plasma glucose [FPG] … and overall low rates of hypoglycemia,” Dr. Vanita Aroda of MedStar Health Research Institute in Hyattsville, Md., said at the annual meeting of the European Association for the Study of Diabetes.

IDeg (Tresiba, Novo Nordisk) is an ultra-long-acting basal insulin analogue currently approved for use in Europe and some other countries around the world. A dual, once-daily, single-injection formulation of IDeg and liraglutide (Xultophy, Novo Nordisk) also is under investigation.

Results from the DUAL (Dual Action of Liraglutide and Insulin Degludec in Type 2 Diabetes) program with the fixed dose combination were reported elsewhere at the EASD annual meeting and recently reported (Lancet Diabetes Endocrinol. 2014 Sept. 2 [doi:10.1016/S2213-8587(14)70174-3]).

In the present study, Dr. Aroda and her associates aimed to confirm the efficacy and safety of IDeg given separately but in combination with liraglutide and metformin versus these oral antidiabetic drugs (OADs) plus an injected insulin placebo.

A total of 1,504 patients with diabetes of at least 6 months’ duration, being treated with metformin or other OADs but not insulin, and in need of treatment intensification were screen for possible inclusion in the trial.

After a 15-week run-in period, during which time the dose of liraglutide was titrated up to 1.5 mg, 346 patients were randomized to receive liraglutide plus metformin and either IDeg or an injectable placebo.

Ninety-two percent of the 174 patients randomized to IDeg plus liraglutide and metformin completed the 26-week trial, as did 76% of the 172 randomized to the placebo arm. Baseline characteristics of the two groups of patients were similar, with a mean age of 57 years, 9 years’ diabetes duration, and a starting HbA_1c of about 7.5%.

FPG values at baseline were 8.7 mmol/L in the intensified arm and 9.1 mmol/L in the placebo arm. These decreased to 8.8 and 6.1 mmol/L, respectively, with an end-of-treatment difference of –2.55 mmol/L favoring the intensified arm, a highly significant difference.

Daily insulin doses at the end of treatment were 51 units in the intensified arm and the equivalent of 105 units in the placebo arm.

Mean body weight was lower in the IDeg-supplemented arm than in the placebo arm at baseline (90.7 kg vs. 94.2 kg), and there was an average weight gain of 2 kg and weight loss of 1.3 kg in each arm, respectively, over the study period, such that the mean body weight at the end of the trial was the same, at 92.7 kg.

No cases of severe hypoglycemia were reported, and there was no significant difference in the number of confirmed nocturnal hypoglycemia cases (four events in three patients with IDeg versus two events in two patients with placebo). The rate of confirmed hypoglycemia was significantly higher in insulin-treated patients (17.3% vs 4.7%); otherwise, both regimens studied were well tolerated.

Dr. Julio Rosenstock of Dallas Diabetes & Endocrine Center, who chaired the session, said that these results were “impressive” and that the study was much better designed than was a similar study with insulin detemir (Levemir, Novo Nordisk) added to liraglutide.

“This is better because you have a control injectable,” he said. “In the previous study with detemir the A_1c came down to 7.1% after 6 months, as reported by DeVries [Diabetes Care 2012;35:1446-54], and to 7.2%, as we reported, after 1 year [J. Diabetes Complications 2013;27:492-500].

“In that previous study the dose of detemir was 39 units, here it was 51 units, so the question is, are the better results because of a higher insulin dose, or because of a difference in the insulin?”

Dr. Rosenstock suggested that a head-to-head trial of insulin detemir and IDeg would be needed to determine the answer. Dr. Aroda agreed.

Dr. Aroda and Dr. Rosenstock disclosed ties with Novo Nordisk, which funded the study, and with other companies that manufacture diabetes medications and devices.

VIENNA – A concerning number of women with gestational diabetes may not be getting optimal retinal care during their pregnancy.

About 11% of women in an Irish observational cohort study received just one retinal exam of the two that are recommended during pregnancy and 29% received no exam, Dr. Aoife Maria Egan said at the annual meeting of the European Association for the Study of Diabetes.

Women who attended prepregnancy care clinics were most likely to get appropriate screening. “This is probably because they had been made aware of what would be expected for them during pregnancy,” said Dr. Egan of the University Hospital Galway (Ireland).

Michele G. Sullivan/Frontline Medical News

The study was an offshoot of the ongoing Atlantic Diabetes in Pregnancy (DIP) project, which examines the outcomes of pregnancy for women with type 1 and type 2 diabetes and the factors influencing these outcomes. It was created in 2005 and provides universal screening for gestational diabetes as part of its outcomes research. The retinopathy study covered 2006-2012.

Adequate retinopathy evaluation was considered to be at least two retinal exams conducted in separate trimesters. Each exam consisted of tests of visual acuity, dilation, and opthalmologic exams and retinal images that were reviewed by an accredited retinal grader.

DIP considered four grades of retinopathy, which have been defined by the National Screening Committee in the United Kingdom: none (R0), background (R1), preproliferative (R2), and proliferative (R3). Additionally, macular edema is graded as present or absent. Progression was considered to be a change from one retinopathy grade to the next or the development of new macular edema.

The study group consisted of 341 women with gestational diabetes (68% type 1). Most of these (90%) were white. They averaged 31 years of age, with a history of two pregnancies. There were 296 live births (87%). The final analysis included 307 women who delivered after 22 weeks.

Most of the women (60%) did have an adequate evaluation. However, 11% had only one exam and 29% had no exam, Dr. Egan said.

There were a few significant differences between those who had adequate retinal exams and those who did not. Women who had two exams were more likely to have type 1 diabetes (72% vs. 61% without adequate exams) and white (94% vs. 85%). They had a longer duration of diabetics (11 vs. 9 years). More of them had attended a prepregnancy center (56% vs. 17%) and were taking folic acid (70% vs. 54%), she reported.

A multivariate analysis determined that attending the prepregnancy clinic was the strongest predictive factor, increasing the likelihood of adequate screening by more than six times.

Of those who had an adequate exam, 74% did not progress during their pregnancy and 26% did. Of those 48 who progressed, the largest portion (26) went from R0 to R1. R1 to R2 progression occurred in seven patients, and R1/R2 to R3 in six. Six patients developed a new maculopathy and three had worsening maculopathy.

Several significant differences emerged when comparing those who progressed with those who did not. The women with worsening retinopathy had a longer duration of diabetes (14 vs. 10 years) and higher systolic blood pressure at baseline (129 vs. 122 mm Hg).

They also had higher baseline hemoglobin A1c (7.7% vs. 7%) and a greater change in HbA1cduring the pregnancy (1.38% vs. 0.74%). An HbA1creduction between the first and third trimester was associated with a doubling in the risk of progression. Those who had a higher reduction of HbA1cbetween trimesters one and three were more than twice as likely to have retinopathy progression.

This highlights the dilemma clinicians face when trying to balance maternal and fetal risks of glycemic control, Dr. Egan said. Women who present with poor glycemic control should moderate that to optimize fetal health, but lowering HbA1ccan predispose the mother to retinopathic changes.

“We try and target tight control and monitor the ones we know are at risk for retinopathy progression very closely,” she said.

Whether that makes any long-term difference is still an unknown. “Some studies have shown that, while pregnancy might accelerate retinopathy, in the long run women end up even in that regard. Six or seven years down the road, everyone looks the same,” she noted.

The DIP program is funded by the Health Research Board of Ireland. Dr. Egan had no financial disclosures.

[email protected]

On Twitter @alz_gal

VIENNA – A concerning number of women with gestational diabetes may not be getting optimal retinal care during their pregnancy.

About 11% of women in an Irish observational cohort study received just one retinal exam of the two that are recommended during pregnancy and 29% received no exam, Dr. Aoife Maria Egan said at the annual meeting of the European Association for the Study of Diabetes.

Women who attended prepregnancy care clinics were most likely to get appropriate screening. “This is probably because they had been made aware of what would be expected for them during pregnancy,” said Dr. Egan of the University Hospital Galway (Ireland).

Michele G. Sullivan/Frontline Medical News

The study was an offshoot of the ongoing Atlantic Diabetes in Pregnancy (DIP) project, which examines the outcomes of pregnancy for women with type 1 and type 2 diabetes and the factors influencing these outcomes. It was created in 2005 and provides universal screening for gestational diabetes as part of its outcomes research. The retinopathy study covered 2006-2012.

Adequate retinopathy evaluation was considered to be at least two retinal exams conducted in separate trimesters. Each exam consisted of tests of visual acuity, dilation, and opthalmologic exams and retinal images that were reviewed by an accredited retinal grader.

DIP considered four grades of retinopathy, which have been defined by the National Screening Committee in the United Kingdom: none (R0), background (R1), preproliferative (R2), and proliferative (R3). Additionally, macular edema is graded as present or absent. Progression was considered to be a change from one retinopathy grade to the next or the development of new macular edema.

The study group consisted of 341 women with gestational diabetes (68% type 1). Most of these (90%) were white. They averaged 31 years of age, with a history of two pregnancies. There were 296 live births (87%). The final analysis included 307 women who delivered after 22 weeks.

Most of the women (60%) did have an adequate evaluation. However, 11% had only one exam and 29% had no exam, Dr. Egan said.

There were a few significant differences between those who had adequate retinal exams and those who did not. Women who had two exams were more likely to have type 1 diabetes (72% vs. 61% without adequate exams) and white (94% vs. 85%). They had a longer duration of diabetics (11 vs. 9 years). More of them had attended a prepregnancy center (56% vs. 17%) and were taking folic acid (70% vs. 54%), she reported.

A multivariate analysis determined that attending the prepregnancy clinic was the strongest predictive factor, increasing the likelihood of adequate screening by more than six times.

Of those who had an adequate exam, 74% did not progress during their pregnancy and 26% did. Of those 48 who progressed, the largest portion (26) went from R0 to R1. R1 to R2 progression occurred in seven patients, and R1/R2 to R3 in six. Six patients developed a new maculopathy and three had worsening maculopathy.

Several significant differences emerged when comparing those who progressed with those who did not. The women with worsening retinopathy had a longer duration of diabetes (14 vs. 10 years) and higher systolic blood pressure at baseline (129 vs. 122 mm Hg).

They also had higher baseline hemoglobin A1c (7.7% vs. 7%) and a greater change in HbA1cduring the pregnancy (1.38% vs. 0.74%). An HbA1creduction between the first and third trimester was associated with a doubling in the risk of progression. Those who had a higher reduction of HbA1cbetween trimesters one and three were more than twice as likely to have retinopathy progression.

This highlights the dilemma clinicians face when trying to balance maternal and fetal risks of glycemic control, Dr. Egan said. Women who present with poor glycemic control should moderate that to optimize fetal health, but lowering HbA1ccan predispose the mother to retinopathic changes.

“We try and target tight control and monitor the ones we know are at risk for retinopathy progression very closely,” she said.

Whether that makes any long-term difference is still an unknown. “Some studies have shown that, while pregnancy might accelerate retinopathy, in the long run women end up even in that regard. Six or seven years down the road, everyone looks the same,” she noted.

The DIP program is funded by the Health Research Board of Ireland. Dr. Egan had no financial disclosures.

[email protected]

On Twitter @alz_gal

VIENNA – A concerning number of women with gestational diabetes may not be getting optimal retinal care during their pregnancy.

About 11% of women in an Irish observational cohort study received just one retinal exam of the two that are recommended during pregnancy and 29% received no exam, Dr. Aoife Maria Egan said at the annual meeting of the European Association for the Study of Diabetes.

Women who attended prepregnancy care clinics were most likely to get appropriate screening. “This is probably because they had been made aware of what would be expected for them during pregnancy,” said Dr. Egan of the University Hospital Galway (Ireland).

Michele G. Sullivan/Frontline Medical News

The study was an offshoot of the ongoing Atlantic Diabetes in Pregnancy (DIP) project, which examines the outcomes of pregnancy for women with type 1 and type 2 diabetes and the factors influencing these outcomes. It was created in 2005 and provides universal screening for gestational diabetes as part of its outcomes research. The retinopathy study covered 2006-2012.

Adequate retinopathy evaluation was considered to be at least two retinal exams conducted in separate trimesters. Each exam consisted of tests of visual acuity, dilation, and opthalmologic exams and retinal images that were reviewed by an accredited retinal grader.

DIP considered four grades of retinopathy, which have been defined by the National Screening Committee in the United Kingdom: none (R0), background (R1), preproliferative (R2), and proliferative (R3). Additionally, macular edema is graded as present or absent. Progression was considered to be a change from one retinopathy grade to the next or the development of new macular edema.

The study group consisted of 341 women with gestational diabetes (68% type 1). Most of these (90%) were white. They averaged 31 years of age, with a history of two pregnancies. There were 296 live births (87%). The final analysis included 307 women who delivered after 22 weeks.

Most of the women (60%) did have an adequate evaluation. However, 11% had only one exam and 29% had no exam, Dr. Egan said.

There were a few significant differences between those who had adequate retinal exams and those who did not. Women who had two exams were more likely to have type 1 diabetes (72% vs. 61% without adequate exams) and white (94% vs. 85%). They had a longer duration of diabetics (11 vs. 9 years). More of them had attended a prepregnancy center (56% vs. 17%) and were taking folic acid (70% vs. 54%), she reported.

A multivariate analysis determined that attending the prepregnancy clinic was the strongest predictive factor, increasing the likelihood of adequate screening by more than six times.

Of those who had an adequate exam, 74% did not progress during their pregnancy and 26% did. Of those 48 who progressed, the largest portion (26) went from R0 to R1. R1 to R2 progression occurred in seven patients, and R1/R2 to R3 in six. Six patients developed a new maculopathy and three had worsening maculopathy.

Several significant differences emerged when comparing those who progressed with those who did not. The women with worsening retinopathy had a longer duration of diabetes (14 vs. 10 years) and higher systolic blood pressure at baseline (129 vs. 122 mm Hg).

They also had higher baseline hemoglobin A1c (7.7% vs. 7%) and a greater change in HbA1cduring the pregnancy (1.38% vs. 0.74%). An HbA1creduction between the first and third trimester was associated with a doubling in the risk of progression. Those who had a higher reduction of HbA1cbetween trimesters one and three were more than twice as likely to have retinopathy progression.

This highlights the dilemma clinicians face when trying to balance maternal and fetal risks of glycemic control, Dr. Egan said. Women who present with poor glycemic control should moderate that to optimize fetal health, but lowering HbA1ccan predispose the mother to retinopathic changes.

“We try and target tight control and monitor the ones we know are at risk for retinopathy progression very closely,” she said.

Whether that makes any long-term difference is still an unknown. “Some studies have shown that, while pregnancy might accelerate retinopathy, in the long run women end up even in that regard. Six or seven years down the road, everyone looks the same,” she noted.

The DIP program is funded by the Health Research Board of Ireland. Dr. Egan had no financial disclosures.

[email protected]

On Twitter @alz_gal

VIENNA – By age 4 years, the children of women who were overweight or obese before their pregnancy scored 3-4 points below normal on measures of neurocognitive development.

The children showed deficits in motor and memory scales, as well as in general cognition, Dr. Leda Chatzi said at the annual meeting of the European Association for the Study of Diabetes.

Children whose mothers had gestational diabetes did not exhibit similar decreased cognitive scores. They were, however, significantly more likely to exhibit symptoms of attention-deficit/hyperactivity disorder, said Dr. Chatzi of the University of Crete, Heraklion, Greece.

“These findings have important public health implications, given the increasing prevalence of maternal obesity and gestational diabetes worldwide,” she said.

Dr. Chatzi presented a subanalysis of the Rhea Study, a mother-child birth cohort that began in Crete in 2007 with the aim of investigating the potential risks maternal environment and lifestyle might exert upon offspring – including maternal obesity. It comprises about 1,300 live singleton births. At entry, mothers give urine and blood samples and undergo anthropometric measurements. Cord blood is collected at birth. Mothers and children are followed from birth onward with anthropometrics, psychological and clinical exams, neurodevelopmental testing, and further biological samples. The oldest children in the cohort are now 7 years old; follow-up continues.

Dr. Chatzi’s study comprised 707 mother-child pairs; the children were 4 years old at the time of this analysis. Maternal factors considered in the analysis included fasting glucose and insulin levels at gestational weeks 10-14, body mass index before pregnancy and at the end of the first trimester, and the development of gestational diabetes.

The children underwent several tests of neurocognition, including the McCarthy Scales of Children’s Abilities; the Attentional Deficit Hyperactivity Disorder Test; and the Strengths and Difficulties Questionnaire.

The McCarthy scale includes several subscales: perceptual, quantitative, motor, verbal, memory, and general cognition. A multivariate analysis controlled for the child’s gender, body mass index (BMI), and preschool attendance; maternal demographics and smoking; and the duration of breastfeeding.

At delivery, mothers had a mean age of 30 years; 32% smoked during pregnancy. The infants’ mean gestational age was 38 weeks. Breastfeeding lasted a mean of 4 months.

About one-third of the mothers were either overweight (21%) or obese (13%). Most of those (92%) developed gestational diabetes.

As maternal prepregnancy BMI increased, child scores on general cognition, memory, and motor subscales decreased. The break point for decline below population norms seemed to be between 25 and 30 kg/m2. The children of women whose prepregnancy BMI approached 40 kg/m2 scored a mean of 3-4 points lower on general cognition and the subscales of memory, quantitative, perceptual, and motor performance.

Prepregnancy BMI had no effect on attention-deficit/hyperactivity disorder scores. However, ADHD scores increased significantly in the children of mothers who developed gestational diabetes.

The pathophysiologic link between gestational diabetes and ADHD has never been elucidated, Dr. Chatzi noted. It’s something she intends to investigate. “We’re planning to evaluate these children at later ages, including studying inflammatory markers and potential genetic markers of DNA methylation,” she said.

Dr. Chatzi had no financial disclosures.

[email protected]

On Twitter @alz_gal

VIENNA – By age 4 years, the children of women who were overweight or obese before their pregnancy scored 3-4 points below normal on measures of neurocognitive development.

The children showed deficits in motor and memory scales, as well as in general cognition, Dr. Leda Chatzi said at the annual meeting of the European Association for the Study of Diabetes.

Children whose mothers had gestational diabetes did not exhibit similar decreased cognitive scores. They were, however, significantly more likely to exhibit symptoms of attention-deficit/hyperactivity disorder, said Dr. Chatzi of the University of Crete, Heraklion, Greece.

“These findings have important public health implications, given the increasing prevalence of maternal obesity and gestational diabetes worldwide,” she said.

Dr. Chatzi presented a subanalysis of the Rhea Study, a mother-child birth cohort that began in Crete in 2007 with the aim of investigating the potential risks maternal environment and lifestyle might exert upon offspring – including maternal obesity. It comprises about 1,300 live singleton births. At entry, mothers give urine and blood samples and undergo anthropometric measurements. Cord blood is collected at birth. Mothers and children are followed from birth onward with anthropometrics, psychological and clinical exams, neurodevelopmental testing, and further biological samples. The oldest children in the cohort are now 7 years old; follow-up continues.

Dr. Chatzi’s study comprised 707 mother-child pairs; the children were 4 years old at the time of this analysis. Maternal factors considered in the analysis included fasting glucose and insulin levels at gestational weeks 10-14, body mass index before pregnancy and at the end of the first trimester, and the development of gestational diabetes.

The children underwent several tests of neurocognition, including the McCarthy Scales of Children’s Abilities; the Attentional Deficit Hyperactivity Disorder Test; and the Strengths and Difficulties Questionnaire.

The McCarthy scale includes several subscales: perceptual, quantitative, motor, verbal, memory, and general cognition. A multivariate analysis controlled for the child’s gender, body mass index (BMI), and preschool attendance; maternal demographics and smoking; and the duration of breastfeeding.

At delivery, mothers had a mean age of 30 years; 32% smoked during pregnancy. The infants’ mean gestational age was 38 weeks. Breastfeeding lasted a mean of 4 months.

About one-third of the mothers were either overweight (21%) or obese (13%). Most of those (92%) developed gestational diabetes.

As maternal prepregnancy BMI increased, child scores on general cognition, memory, and motor subscales decreased. The break point for decline below population norms seemed to be between 25 and 30 kg/m2. The children of women whose prepregnancy BMI approached 40 kg/m2 scored a mean of 3-4 points lower on general cognition and the subscales of memory, quantitative, perceptual, and motor performance.

Prepregnancy BMI had no effect on attention-deficit/hyperactivity disorder scores. However, ADHD scores increased significantly in the children of mothers who developed gestational diabetes.

The pathophysiologic link between gestational diabetes and ADHD has never been elucidated, Dr. Chatzi noted. It’s something she intends to investigate. “We’re planning to evaluate these children at later ages, including studying inflammatory markers and potential genetic markers of DNA methylation,” she said.

Dr. Chatzi had no financial disclosures.

[email protected]

On Twitter @alz_gal

VIENNA – By age 4 years, the children of women who were overweight or obese before their pregnancy scored 3-4 points below normal on measures of neurocognitive development.

The children showed deficits in motor and memory scales, as well as in general cognition, Dr. Leda Chatzi said at the annual meeting of the European Association for the Study of Diabetes.

Children whose mothers had gestational diabetes did not exhibit similar decreased cognitive scores. They were, however, significantly more likely to exhibit symptoms of attention-deficit/hyperactivity disorder, said Dr. Chatzi of the University of Crete, Heraklion, Greece.

“These findings have important public health implications, given the increasing prevalence of maternal obesity and gestational diabetes worldwide,” she said.

Dr. Chatzi presented a subanalysis of the Rhea Study, a mother-child birth cohort that began in Crete in 2007 with the aim of investigating the potential risks maternal environment and lifestyle might exert upon offspring – including maternal obesity. It comprises about 1,300 live singleton births. At entry, mothers give urine and blood samples and undergo anthropometric measurements. Cord blood is collected at birth. Mothers and children are followed from birth onward with anthropometrics, psychological and clinical exams, neurodevelopmental testing, and further biological samples. The oldest children in the cohort are now 7 years old; follow-up continues.

Dr. Chatzi’s study comprised 707 mother-child pairs; the children were 4 years old at the time of this analysis. Maternal factors considered in the analysis included fasting glucose and insulin levels at gestational weeks 10-14, body mass index before pregnancy and at the end of the first trimester, and the development of gestational diabetes.

The children underwent several tests of neurocognition, including the McCarthy Scales of Children’s Abilities; the Attentional Deficit Hyperactivity Disorder Test; and the Strengths and Difficulties Questionnaire.

The McCarthy scale includes several subscales: perceptual, quantitative, motor, verbal, memory, and general cognition. A multivariate analysis controlled for the child’s gender, body mass index (BMI), and preschool attendance; maternal demographics and smoking; and the duration of breastfeeding.

At delivery, mothers had a mean age of 30 years; 32% smoked during pregnancy. The infants’ mean gestational age was 38 weeks. Breastfeeding lasted a mean of 4 months.

About one-third of the mothers were either overweight (21%) or obese (13%). Most of those (92%) developed gestational diabetes.

As maternal prepregnancy BMI increased, child scores on general cognition, memory, and motor subscales decreased. The break point for decline below population norms seemed to be between 25 and 30 kg/m2. The children of women whose prepregnancy BMI approached 40 kg/m2 scored a mean of 3-4 points lower on general cognition and the subscales of memory, quantitative, perceptual, and motor performance.

Prepregnancy BMI had no effect on attention-deficit/hyperactivity disorder scores. However, ADHD scores increased significantly in the children of mothers who developed gestational diabetes.

The pathophysiologic link between gestational diabetes and ADHD has never been elucidated, Dr. Chatzi noted. It’s something she intends to investigate. “We’re planning to evaluate these children at later ages, including studying inflammatory markers and potential genetic markers of DNA methylation,” she said.

Dr. Chatzi had no financial disclosures.

[email protected]

On Twitter @alz_gal

VIENNA – Two separate analyses of data from the Dutch-based, longitudinal Diabetes Care System cohort show that there are four distinct, but not necessarily related, subgroups of patients with type 2 diabetes based on hemoglobin A1C and systolic blood pressure over time.

Both analyses showed that, on the whole, most patients with type 2 diabetes are well controlled, with 83% hitting a European guideline–directed A1C target of 7% or less and 86% achieving adequate (140 mm Hg or lower) systolic blood pressure (SBP) control, both after a mean follow-up of 5.7 years.

However, there were two distinct subgroups of patients in both analyses who did not achieve good A1C or SBP control, with a fourth group showing a delayed response to therapy.

“This is the start of a new analysis,” said Dr. Giel Nijpels of the VU University Medical Center in Amsterdam where the research was coordinated. “We plan to do dynamic prediction models,” he added, with the aim of “more individualized prediction of patient level of risk.”

Patients with type 2 diabetes are at increased risk for both micro- and macrovascular complications, Dr. Nijpels said at the annual meeting of the European Association for the Study of Diabetes. However, “what every doctor knows, especially primary care physicians, is that not every patient with type 2 diabetes has the same risk.”

Guidelines do not take the individual characteristics into account and recommend fixed targets for both glucose and blood pressure control. These targets are based on randomized, controlled trial data, which do not reflect “real world” clinical practice, he observed. Since type 2 diabetes is a heterogeneous disease, and clearly “one size does not fit all,” there was a need to look at the trajectories of both blood glucose and blood pressure control, to see if there are any changes over time that may help to identify patients that may need a little extra help to achieve their personalized targets.

The Diabetes Care System cohort was initiated in 1998 and is a centrally organized diabetes care system. There are currently 9,849 patients with types 2 diabetes registered in the system, who were included anytime from the start of the program until 2012. Patients undergo a physical examination at recruitment and glycemic, blood pressure, and other key parameters are recorded at this baseline. Patients are then checked annually, providing a longitudinal source of real-world data.

For the analysis of blood glucose control, which Dr. Nijpels presented, patients had to have at least two A1C follow-up measurements; 5,423 patients were included. For the analysis of blood pressure control, presented by his college Dr. Iris Walraven, at least two SBP follow-up measurements were needed; 5,711 patients fulfilled this criteria.

The four subgroups of patients based on glycemic control were labeled “good glycemic control,” “fast responders,” “reduced glycemic control,” and “nonresponders.” There were 83.1%, 8.2%, 5.2%, and 3.4% in each group, respectively. The good glycemic control group maintained a target A1C of 7% or lower throughout the follow-up period, which was up to a maximum of 9 years. As the name suggests, the 8.2% of patients in the fast responders group experienced a rapid drop in A1C in the first 2 years of treatment, and then maintained a target A1C for the duration of follow-up. The 5.2% of patients with reduced glycemic control exhibited an initial A1C decrease very close to target, but this subsequently rose further away from the desired target during follow-up, and the 3.4% who were “nonresponders” failed to achieved a target A1C throughout the course of their treatment.

Analysis showed that the fast responders tended to have significantly higher A1C values at baseline, compared with the reduced glycemic control or nonresponsive subgroups, with comparable A1C to those in the “good glycemic control” subgroup. Patients in the reduced control and nonresponder subgroups tended to be younger (under 60 years of age) and have a longer diabetes duration (more than 1 year), with a higher prevalence of microvascular complications than the good or fast control groups, Dr. Nijpels reported.

In terms of treatment, most patients were “doing well” on metformin alone, sulfonylurea monotherapy, or on both of those, with about a quarter of patients using insulin.

Four subgroups of patients with distinct SBP control over time were also identified, although they were not directly linked to the four glycemic control subgroups, said Dr. Walraven in an interview. She noted that while the majority (85.6%) of patients fell into the “adequate SBP control” group, achieving a guideline-recommend systolic blood pressure of 140 mm Hg or lower, 5.6% were “delayed responders,” 3.4% were “insufficient responders,” and 3.4% were “nonresponders.”

When the delayed responders were compared with the adequate responders, they tended to be older (66 vs. 59 years) and have higher body mass indexes (31 kg/m² vs. 29 kg/m²). The insufficient responders were also older and had higher body weight, and were also more likely to be female than male (68% vs. 47%), compared with the adequate responders). Nonresponders were also more likely to be women, of older age, and have a longer diabetes duration (2 vs. 0.9 years).

Dr. Walraven reported that patients with insufficient SBP control had almost a twofold increased risk for cardiovascular disease. “Subgroups with inferior SBP control are important to target in order to eventually improve BP management,” she observed.

Patients’ adherence to medication was questioned in the discussions following both presentations. Although this was not directly measured, Dr. Nijpels responded that, certainly with regard to glucose-lowering agents, that he was “convinced that everyone in this cohort took their medication.”

Dr. Nijpels and Dr. Walraven had no conflicts of interest.

VIENNA – Two separate analyses of data from the Dutch-based, longitudinal Diabetes Care System cohort show that there are four distinct, but not necessarily related, subgroups of patients with type 2 diabetes based on hemoglobin A1C and systolic blood pressure over time.

Both analyses showed that, on the whole, most patients with type 2 diabetes are well controlled, with 83% hitting a European guideline–directed A1C target of 7% or less and 86% achieving adequate (140 mm Hg or lower) systolic blood pressure (SBP) control, both after a mean follow-up of 5.7 years.

However, there were two distinct subgroups of patients in both analyses who did not achieve good A1C or SBP control, with a fourth group showing a delayed response to therapy.

“This is the start of a new analysis,” said Dr. Giel Nijpels of the VU University Medical Center in Amsterdam where the research was coordinated. “We plan to do dynamic prediction models,” he added, with the aim of “more individualized prediction of patient level of risk.”

Patients with type 2 diabetes are at increased risk for both micro- and macrovascular complications, Dr. Nijpels said at the annual meeting of the European Association for the Study of Diabetes. However, “what every doctor knows, especially primary care physicians, is that not every patient with type 2 diabetes has the same risk.”

Guidelines do not take the individual characteristics into account and recommend fixed targets for both glucose and blood pressure control. These targets are based on randomized, controlled trial data, which do not reflect “real world” clinical practice, he observed. Since type 2 diabetes is a heterogeneous disease, and clearly “one size does not fit all,” there was a need to look at the trajectories of both blood glucose and blood pressure control, to see if there are any changes over time that may help to identify patients that may need a little extra help to achieve their personalized targets.

The Diabetes Care System cohort was initiated in 1998 and is a centrally organized diabetes care system. There are currently 9,849 patients with types 2 diabetes registered in the system, who were included anytime from the start of the program until 2012. Patients undergo a physical examination at recruitment and glycemic, blood pressure, and other key parameters are recorded at this baseline. Patients are then checked annually, providing a longitudinal source of real-world data.

For the analysis of blood glucose control, which Dr. Nijpels presented, patients had to have at least two A1C follow-up measurements; 5,423 patients were included. For the analysis of blood pressure control, presented by his college Dr. Iris Walraven, at least two SBP follow-up measurements were needed; 5,711 patients fulfilled this criteria.

The four subgroups of patients based on glycemic control were labeled “good glycemic control,” “fast responders,” “reduced glycemic control,” and “nonresponders.” There were 83.1%, 8.2%, 5.2%, and 3.4% in each group, respectively. The good glycemic control group maintained a target A1C of 7% or lower throughout the follow-up period, which was up to a maximum of 9 years. As the name suggests, the 8.2% of patients in the fast responders group experienced a rapid drop in A1C in the first 2 years of treatment, and then maintained a target A1C for the duration of follow-up. The 5.2% of patients with reduced glycemic control exhibited an initial A1C decrease very close to target, but this subsequently rose further away from the desired target during follow-up, and the 3.4% who were “nonresponders” failed to achieved a target A1C throughout the course of their treatment.

Analysis showed that the fast responders tended to have significantly higher A1C values at baseline, compared with the reduced glycemic control or nonresponsive subgroups, with comparable A1C to those in the “good glycemic control” subgroup. Patients in the reduced control and nonresponder subgroups tended to be younger (under 60 years of age) and have a longer diabetes duration (more than 1 year), with a higher prevalence of microvascular complications than the good or fast control groups, Dr. Nijpels reported.

In terms of treatment, most patients were “doing well” on metformin alone, sulfonylurea monotherapy, or on both of those, with about a quarter of patients using insulin.

Four subgroups of patients with distinct SBP control over time were also identified, although they were not directly linked to the four glycemic control subgroups, said Dr. Walraven in an interview. She noted that while the majority (85.6%) of patients fell into the “adequate SBP control” group, achieving a guideline-recommend systolic blood pressure of 140 mm Hg or lower, 5.6% were “delayed responders,” 3.4% were “insufficient responders,” and 3.4% were “nonresponders.”

When the delayed responders were compared with the adequate responders, they tended to be older (66 vs. 59 years) and have higher body mass indexes (31 kg/m² vs. 29 kg/m²). The insufficient responders were also older and had higher body weight, and were also more likely to be female than male (68% vs. 47%), compared with the adequate responders). Nonresponders were also more likely to be women, of older age, and have a longer diabetes duration (2 vs. 0.9 years).

Dr. Walraven reported that patients with insufficient SBP control had almost a twofold increased risk for cardiovascular disease. “Subgroups with inferior SBP control are important to target in order to eventually improve BP management,” she observed.

Patients’ adherence to medication was questioned in the discussions following both presentations. Although this was not directly measured, Dr. Nijpels responded that, certainly with regard to glucose-lowering agents, that he was “convinced that everyone in this cohort took their medication.”

Dr. Nijpels and Dr. Walraven had no conflicts of interest.

VIENNA – Two separate analyses of data from the Dutch-based, longitudinal Diabetes Care System cohort show that there are four distinct, but not necessarily related, subgroups of patients with type 2 diabetes based on hemoglobin A1C and systolic blood pressure over time.

Both analyses showed that, on the whole, most patients with type 2 diabetes are well controlled, with 83% hitting a European guideline–directed A1C target of 7% or less and 86% achieving adequate (140 mm Hg or lower) systolic blood pressure (SBP) control, both after a mean follow-up of 5.7 years.

However, there were two distinct subgroups of patients in both analyses who did not achieve good A1C or SBP control, with a fourth group showing a delayed response to therapy.

“This is the start of a new analysis,” said Dr. Giel Nijpels of the VU University Medical Center in Amsterdam where the research was coordinated. “We plan to do dynamic prediction models,” he added, with the aim of “more individualized prediction of patient level of risk.”

Patients with type 2 diabetes are at increased risk for both micro- and macrovascular complications, Dr. Nijpels said at the annual meeting of the European Association for the Study of Diabetes. However, “what every doctor knows, especially primary care physicians, is that not every patient with type 2 diabetes has the same risk.”

Guidelines do not take the individual characteristics into account and recommend fixed targets for both glucose and blood pressure control. These targets are based on randomized, controlled trial data, which do not reflect “real world” clinical practice, he observed. Since type 2 diabetes is a heterogeneous disease, and clearly “one size does not fit all,” there was a need to look at the trajectories of both blood glucose and blood pressure control, to see if there are any changes over time that may help to identify patients that may need a little extra help to achieve their personalized targets.

The Diabetes Care System cohort was initiated in 1998 and is a centrally organized diabetes care system. There are currently 9,849 patients with types 2 diabetes registered in the system, who were included anytime from the start of the program until 2012. Patients undergo a physical examination at recruitment and glycemic, blood pressure, and other key parameters are recorded at this baseline. Patients are then checked annually, providing a longitudinal source of real-world data.

For the analysis of blood glucose control, which Dr. Nijpels presented, patients had to have at least two A1C follow-up measurements; 5,423 patients were included. For the analysis of blood pressure control, presented by his college Dr. Iris Walraven, at least two SBP follow-up measurements were needed; 5,711 patients fulfilled this criteria.

The four subgroups of patients based on glycemic control were labeled “good glycemic control,” “fast responders,” “reduced glycemic control,” and “nonresponders.” There were 83.1%, 8.2%, 5.2%, and 3.4% in each group, respectively. The good glycemic control group maintained a target A1C of 7% or lower throughout the follow-up period, which was up to a maximum of 9 years. As the name suggests, the 8.2% of patients in the fast responders group experienced a rapid drop in A1C in the first 2 years of treatment, and then maintained a target A1C for the duration of follow-up. The 5.2% of patients with reduced glycemic control exhibited an initial A1C decrease very close to target, but this subsequently rose further away from the desired target during follow-up, and the 3.4% who were “nonresponders” failed to achieved a target A1C throughout the course of their treatment.

Analysis showed that the fast responders tended to have significantly higher A1C values at baseline, compared with the reduced glycemic control or nonresponsive subgroups, with comparable A1C to those in the “good glycemic control” subgroup. Patients in the reduced control and nonresponder subgroups tended to be younger (under 60 years of age) and have a longer diabetes duration (more than 1 year), with a higher prevalence of microvascular complications than the good or fast control groups, Dr. Nijpels reported.

In terms of treatment, most patients were “doing well” on metformin alone, sulfonylurea monotherapy, or on both of those, with about a quarter of patients using insulin.

Four subgroups of patients with distinct SBP control over time were also identified, although they were not directly linked to the four glycemic control subgroups, said Dr. Walraven in an interview. She noted that while the majority (85.6%) of patients fell into the “adequate SBP control” group, achieving a guideline-recommend systolic blood pressure of 140 mm Hg or lower, 5.6% were “delayed responders,” 3.4% were “insufficient responders,” and 3.4% were “nonresponders.”

When the delayed responders were compared with the adequate responders, they tended to be older (66 vs. 59 years) and have higher body mass indexes (31 kg/m² vs. 29 kg/m²). The insufficient responders were also older and had higher body weight, and were also more likely to be female than male (68% vs. 47%), compared with the adequate responders). Nonresponders were also more likely to be women, of older age, and have a longer diabetes duration (2 vs. 0.9 years).

Dr. Walraven reported that patients with insufficient SBP control had almost a twofold increased risk for cardiovascular disease. “Subgroups with inferior SBP control are important to target in order to eventually improve BP management,” she observed.

Patients’ adherence to medication was questioned in the discussions following both presentations. Although this was not directly measured, Dr. Nijpels responded that, certainly with regard to glucose-lowering agents, that he was “convinced that everyone in this cohort took their medication.”

Dr. Nijpels and Dr. Walraven had no conflicts of interest.

VIENNA – Two separate analyses of data from the Dutch-based, longitudinal Diabetes Care System cohort show that there are four distinct, but not necessarily related, subgroups of patients with type 2 diabetes based on hemoglobin A1c and systolic blood pressure over time.

Both analyses showed that, on the whole, most patients with type 2 diabetes are well controlled, with 83% hitting a European guideline–directed HbA1c target of 7% or less and 86% achieving adequate (140 mm Hg or lower) systolic blood pressure (SBP) control, both after a mean follow-up of 5.7 years.

However, there were two distinct subgroups of patients in both analyses who did not achieve good HbA1c or SBP control, with a fourth group showing a delayed response to therapy.

“This is the start of a new analysis,” said Dr. Giel Nijpels of the VU University Medical Center in Amsterdam where the research was coordinated. “We plan to do dynamic prediction models,” he added, with the aim of “more individualized prediction of patient level of risk.”

Patients with type 2 diabetes are at increased risk for both micro- and macrovascular complications, Dr. Nijpels said at the annual meeting of the European Association for the Study of Diabetes. However, “what every doctor knows, especially primary care physicians, is that not every patient with type 2 diabetes has the same risk.”

Guidelines do not take the individual characteristics into account and recommend fixed targets for both glucose and blood pressure control. These targets are based on randomized, controlled trial data, which do not reflect “real world” clinical practice, he observed. Since type 2 diabetes is a heterogeneous disease, and clearly “one size does not fit all,” there was a need to look at the trajectories of both blood glucose and blood pressure control, to see if there are any changes over time that may help to identify patients that may need a little extra help to achieve their personalized targets.

The Diabetes Care System cohort was initiated in 1998 and is a centrally organized diabetes care system. There are currently 9,849 patients with types 2 diabetes registered in the system, who were included anytime from the start of the program until 2012. Patients undergo a physical examination at recruitment and glycemic, blood pressure, and other key parameters are recorded at this baseline. Patients are then checked annually, providing a longitudinal source of real-world data.

For the analysis of blood glucose control, which Dr. Nijpels presented, patients had to have at least two HbA1c follow-up measurements; 5,423 patients were included. For the analysis of blood pressure control, presented by his college Dr. Iris Walraven, at least two SBP follow-up measurements were needed; 5,711 patients fulfilled this criteria.

The four subgroups of patients based on glycemic control were labeled “good glycemic control,” “fast responders,” “reduced glycemic control,” and “nonresponders.” There were 83.1%, 8.2%, 5.2%, and 3.4% in each group, respectively. The good glycemic control group maintained a target HbA1c of 7% or lower throughout the follow-up period, which was up to a maximum of 9 years. As the name suggests, the 8.2% of patients in the fast responders group experienced a rapid drop in HbA1c in the first 2 years of treatment, and then maintained a target HbA_1c for the duration of follow-up. The 5.2% of patients with reduced glycemic control exhibited an initial HbA_1c decrease very close to target, but this subsequently rose further away from the desired target during follow-up, and the 3.4% who were “nonresponders” failed to achieved a target HbA_1c throughout the course of their treatment.

Analysis showed that the fast responders tended to have significantly higher HbA_1c values at baseline, compared with the reduced glycemic control or nonresponsive subgroups, with comparable HbA_1c to those in the “good glycemic control” subgroup. Patients in the reduced control and nonresponder subgroups tended to be younger (under 60 years of age) and have a longer diabetes duration (more than 1 year), with a higher prevalence of microvascular complications than the good or fast control groups, Dr. Nijpels reported.

In terms of treatment, most patients were “doing well” on metformin alone, sulfonylurea monotherapy, or on both of those, with about a quarter of patients using insulin.

Four subgroups of patients with distinct SBP control over time were also identified, although they were not directly linked to the four glycemic control subgroups, said Dr. Walraven in an interview. She noted that while the majority (85.6%) of patients fell into the “adequate SBP control” group, achieving a guideline-recommend systolic blood pressure of 140 mm Hg or lower, 5.6% were “delayed responders,” 3.4% were “insufficient responders,” and 3.4% were “nonresponders.”

When the delayed responders were compared with the adequate responders, they tended to be older (66 vs. 59 years) and have higher body mass indexes (31 kg/m² vs. 29 kg/m²). The insufficient responders were also older and had higher body weight, and were also more likely to be female than male (68% vs. 47%), compared with the adequate responders). Nonresponders were also more likely to be women, of older age, and have a longer diabetes duration (2 vs. 0.9 years).

Dr. Walraven reported that patients with insufficient SBP control had almost a twofold increased risk for cardiovascular disease. “Subgroups with inferior SBP control are important to target in order to eventually improve BP management,” she observed.

Patients’ adherence to medication was questioned in the discussions following both presentations. Although this was not directly measured, Dr. Nijpels responded that, certainly with regard to glucose-lowering agents, that he was “convinced that everyone in this cohort took their medication.”

Dr. Nijpels and Dr. Walraven had no conflicts of interest.

VIENNA – Two separate analyses of data from the Dutch-based, longitudinal Diabetes Care System cohort show that there are four distinct, but not necessarily related, subgroups of patients with type 2 diabetes based on hemoglobin A1c and systolic blood pressure over time.

Both analyses showed that, on the whole, most patients with type 2 diabetes are well controlled, with 83% hitting a European guideline–directed HbA1c target of 7% or less and 86% achieving adequate (140 mm Hg or lower) systolic blood pressure (SBP) control, both after a mean follow-up of 5.7 years.

However, there were two distinct subgroups of patients in both analyses who did not achieve good HbA1c or SBP control, with a fourth group showing a delayed response to therapy.

“This is the start of a new analysis,” said Dr. Giel Nijpels of the VU University Medical Center in Amsterdam where the research was coordinated. “We plan to do dynamic prediction models,” he added, with the aim of “more individualized prediction of patient level of risk.”

Patients with type 2 diabetes are at increased risk for both micro- and macrovascular complications, Dr. Nijpels said at the annual meeting of the European Association for the Study of Diabetes. However, “what every doctor knows, especially primary care physicians, is that not every patient with type 2 diabetes has the same risk.”

Guidelines do not take the individual characteristics into account and recommend fixed targets for both glucose and blood pressure control. These targets are based on randomized, controlled trial data, which do not reflect “real world” clinical practice, he observed. Since type 2 diabetes is a heterogeneous disease, and clearly “one size does not fit all,” there was a need to look at the trajectories of both blood glucose and blood pressure control, to see if there are any changes over time that may help to identify patients that may need a little extra help to achieve their personalized targets.

The Diabetes Care System cohort was initiated in 1998 and is a centrally organized diabetes care system. There are currently 9,849 patients with types 2 diabetes registered in the system, who were included anytime from the start of the program until 2012. Patients undergo a physical examination at recruitment and glycemic, blood pressure, and other key parameters are recorded at this baseline. Patients are then checked annually, providing a longitudinal source of real-world data.

For the analysis of blood glucose control, which Dr. Nijpels presented, patients had to have at least two HbA1c follow-up measurements; 5,423 patients were included. For the analysis of blood pressure control, presented by his college Dr. Iris Walraven, at least two SBP follow-up measurements were needed; 5,711 patients fulfilled this criteria.

The four subgroups of patients based on glycemic control were labeled “good glycemic control,” “fast responders,” “reduced glycemic control,” and “nonresponders.” There were 83.1%, 8.2%, 5.2%, and 3.4% in each group, respectively. The good glycemic control group maintained a target HbA1c of 7% or lower throughout the follow-up period, which was up to a maximum of 9 years. As the name suggests, the 8.2% of patients in the fast responders group experienced a rapid drop in HbA1c in the first 2 years of treatment, and then maintained a target HbA_1c for the duration of follow-up. The 5.2% of patients with reduced glycemic control exhibited an initial HbA_1c decrease very close to target, but this subsequently rose further away from the desired target during follow-up, and the 3.4% who were “nonresponders” failed to achieved a target HbA_1c throughout the course of their treatment.

Analysis showed that the fast responders tended to have significantly higher HbA_1c values at baseline, compared with the reduced glycemic control or nonresponsive subgroups, with comparable HbA_1c to those in the “good glycemic control” subgroup. Patients in the reduced control and nonresponder subgroups tended to be younger (under 60 years of age) and have a longer diabetes duration (more than 1 year), with a higher prevalence of microvascular complications than the good or fast control groups, Dr. Nijpels reported.

In terms of treatment, most patients were “doing well” on metformin alone, sulfonylurea monotherapy, or on both of those, with about a quarter of patients using insulin.

Four subgroups of patients with distinct SBP control over time were also identified, although they were not directly linked to the four glycemic control subgroups, said Dr. Walraven in an interview. She noted that while the majority (85.6%) of patients fell into the “adequate SBP control” group, achieving a guideline-recommend systolic blood pressure of 140 mm Hg or lower, 5.6% were “delayed responders,” 3.4% were “insufficient responders,” and 3.4% were “nonresponders.”

When the delayed responders were compared with the adequate responders, they tended to be older (66 vs. 59 years) and have higher body mass indexes (31 kg/m² vs. 29 kg/m²). The insufficient responders were also older and had higher body weight, and were also more likely to be female than male (68% vs. 47%), compared with the adequate responders). Nonresponders were also more likely to be women, of older age, and have a longer diabetes duration (2 vs. 0.9 years).

Dr. Walraven reported that patients with insufficient SBP control had almost a twofold increased risk for cardiovascular disease. “Subgroups with inferior SBP control are important to target in order to eventually improve BP management,” she observed.

Patients’ adherence to medication was questioned in the discussions following both presentations. Although this was not directly measured, Dr. Nijpels responded that, certainly with regard to glucose-lowering agents, that he was “convinced that everyone in this cohort took their medication.”

Dr. Nijpels and Dr. Walraven had no conflicts of interest.

VIENNA – Two separate analyses of data from the Dutch-based, longitudinal Diabetes Care System cohort show that there are four distinct, but not necessarily related, subgroups of patients with type 2 diabetes based on hemoglobin A1c and systolic blood pressure over time.

Both analyses showed that, on the whole, most patients with type 2 diabetes are well controlled, with 83% hitting a European guideline–directed HbA1c target of 7% or less and 86% achieving adequate (140 mm Hg or lower) systolic blood pressure (SBP) control, both after a mean follow-up of 5.7 years.

However, there were two distinct subgroups of patients in both analyses who did not achieve good HbA1c or SBP control, with a fourth group showing a delayed response to therapy.

“This is the start of a new analysis,” said Dr. Giel Nijpels of the VU University Medical Center in Amsterdam where the research was coordinated. “We plan to do dynamic prediction models,” he added, with the aim of “more individualized prediction of patient level of risk.”

Patients with type 2 diabetes are at increased risk for both micro- and macrovascular complications, Dr. Nijpels said at the annual meeting of the European Association for the Study of Diabetes. However, “what every doctor knows, especially primary care physicians, is that not every patient with type 2 diabetes has the same risk.”

Guidelines do not take the individual characteristics into account and recommend fixed targets for both glucose and blood pressure control. These targets are based on randomized, controlled trial data, which do not reflect “real world” clinical practice, he observed. Since type 2 diabetes is a heterogeneous disease, and clearly “one size does not fit all,” there was a need to look at the trajectories of both blood glucose and blood pressure control, to see if there are any changes over time that may help to identify patients that may need a little extra help to achieve their personalized targets.

The Diabetes Care System cohort was initiated in 1998 and is a centrally organized diabetes care system. There are currently 9,849 patients with types 2 diabetes registered in the system, who were included anytime from the start of the program until 2012. Patients undergo a physical examination at recruitment and glycemic, blood pressure, and other key parameters are recorded at this baseline. Patients are then checked annually, providing a longitudinal source of real-world data.

For the analysis of blood glucose control, which Dr. Nijpels presented, patients had to have at least two HbA1c follow-up measurements; 5,423 patients were included. For the analysis of blood pressure control, presented by his college Dr. Iris Walraven, at least two SBP follow-up measurements were needed; 5,711 patients fulfilled this criteria.

The four subgroups of patients based on glycemic control were labeled “good glycemic control,” “fast responders,” “reduced glycemic control,” and “nonresponders.” There were 83.1%, 8.2%, 5.2%, and 3.4% in each group, respectively. The good glycemic control group maintained a target HbA1c of 7% or lower throughout the follow-up period, which was up to a maximum of 9 years. As the name suggests, the 8.2% of patients in the fast responders group experienced a rapid drop in HbA1c in the first 2 years of treatment, and then maintained a target HbA_1c for the duration of follow-up. The 5.2% of patients with reduced glycemic control exhibited an initial HbA_1c decrease very close to target, but this subsequently rose further away from the desired target during follow-up, and the 3.4% who were “nonresponders” failed to achieved a target HbA_1c throughout the course of their treatment.

Analysis showed that the fast responders tended to have significantly higher HbA_1c values at baseline, compared with the reduced glycemic control or nonresponsive subgroups, with comparable HbA_1c to those in the “good glycemic control” subgroup. Patients in the reduced control and nonresponder subgroups tended to be younger (under 60 years of age) and have a longer diabetes duration (more than 1 year), with a higher prevalence of microvascular complications than the good or fast control groups, Dr. Nijpels reported.

In terms of treatment, most patients were “doing well” on metformin alone, sulfonylurea monotherapy, or on both of those, with about a quarter of patients using insulin.

Four subgroups of patients with distinct SBP control over time were also identified, although they were not directly linked to the four glycemic control subgroups, said Dr. Walraven in an interview. She noted that while the majority (85.6%) of patients fell into the “adequate SBP control” group, achieving a guideline-recommend systolic blood pressure of 140 mm Hg or lower, 5.6% were “delayed responders,” 3.4% were “insufficient responders,” and 3.4% were “nonresponders.”

When the delayed responders were compared with the adequate responders, they tended to be older (66 vs. 59 years) and have higher body mass indexes (31 kg/m² vs. 29 kg/m²). The insufficient responders were also older and had higher body weight, and were also more likely to be female than male (68% vs. 47%), compared with the adequate responders). Nonresponders were also more likely to be women, of older age, and have a longer diabetes duration (2 vs. 0.9 years).

Dr. Walraven reported that patients with insufficient SBP control had almost a twofold increased risk for cardiovascular disease. “Subgroups with inferior SBP control are important to target in order to eventually improve BP management,” she observed.

Patients’ adherence to medication was questioned in the discussions following both presentations. Although this was not directly measured, Dr. Nijpels responded that, certainly with regard to glucose-lowering agents, that he was “convinced that everyone in this cohort took their medication.”

Dr. Nijpels and Dr. Walraven had no conflicts of interest.

VIENNA – A risk model based on a single assessment of hemoglobin A_1c and other parameters was able to differentiate well between patients who had a low and high risk for progression of sight-threatening diabetic retinopathy, researchers reported at the annual meeting of the European Association for the Study of Diabetes.

Although further validation is needed, the risk model “would be suitable for personalized screening intervals,” said presenting author Dr. Irene Stratton of the Gloucestershire (England) Hospitals NHS Foundation Trust. In England, the current recommendation is to screen everyone with diabetes annually using digital retinal photography.

Because of the increasing numbers of patients that require annual screening, health budgets for diabetic eye screening are being stretched and alternatives are desirable. In England, such screening considers both retinopathy and macropathology, Dr. Stratton said.

The risk model was derived and tested based on data from 14,000 patients with no or mild nonproliferative retinopathy treated in the Gloucestershire area. The investigators looked at HbA_1c levels in the 12 months prior to diabetic eye screening to determine if they could predict which patients did and did not develop sight-threatening retinopathy. The risk model also considered the baseline retinopathy status in both eyes of patients; systolic and diastolic blood pressure; measures of kidney function and lipids; the time to develop retinopathy from diagnosis; and the type of diabetes.

“We found that the most important piece of information that went into the model was the grading at the baseline screening episode,” Dr. Stratton said. “So patients who had no retinopathy in either eye were at lowest risk, patients with background retinopathy in one eye had about a doubling of risk, and patients with background retinopathy in both eyes were at a much higher level of risk.”

The next most important parameters were the time since the first mention of a diagnosis of diabetes and HbA_1c in the year prior to screening. Total cholesterol in the year prior to screening also was a factor for consideration.

Hazard ratios for the development of diabetic retinopathy were 7.13 for patients with mild retinopathy in both eyes at baseline and 2.56 for those with mild retinopathy in one eye. The hazard ratios increased by 1.28 for every 10-mmol/mol increase in HbA_1c in the past 12 months, by 1.20 for every 5-year increase in the duration of diabetes, and by 1.12 for every 1-mmol/L increase in total serum cholesterol.

Three study populations, which altogether comprised almost 20,000 patients with diabetes, were used to validate the model; the largest population included more than 17,000 individuals. The main difference between the screening programs was the ethnic mix, Dr. Stratton highlighted. White patients dominated in the largest screening cohort, at 98%, but to a lesser extent in the other cohorts, at 47% (of 1,223 patients) and 81% (of 1,083). About half the patients in the cohorts were women, and the duration of diabetes ranged from 2.9 to 4.5 years. The majority (95%) of patients screened had type 1 diabetes. HbA_1c ranged from 6.3% to 8.2% overall.

The investigators stratified patients according to quintiles of risk using the model, and found that the quintiles correlated very well with the chances of patients developing sight-threatening eye disease in each of the three validation cohorts. Comparing the lowest- with the highest-risk quintiles, the rate of progression to sight-threatening retinopathy was 1-3 and 55-79 per 1,000 per patient-years, respectively. The overall event rate was around 20 per 1,000 patient years.

“Further validation in other screening programs and ethnic groups is required,” Dr. Stratton concluded.

The study was funded by a grant from the U.K. National Institute for Health Research, Health Technology Assessment Programme; and the Gloucestershire Hospitals National Health Service Foundation Trust. Dr. Stratton had no conflicts of interest.

VIENNA – A risk model based on a single assessment of hemoglobin A_1c and other parameters was able to differentiate well between patients who had a low and high risk for progression of sight-threatening diabetic retinopathy, researchers reported at the annual meeting of the European Association for the Study of Diabetes.

Although further validation is needed, the risk model “would be suitable for personalized screening intervals,” said presenting author Dr. Irene Stratton of the Gloucestershire (England) Hospitals NHS Foundation Trust. In England, the current recommendation is to screen everyone with diabetes annually using digital retinal photography.

Because of the increasing numbers of patients that require annual screening, health budgets for diabetic eye screening are being stretched and alternatives are desirable. In England, such screening considers both retinopathy and macropathology, Dr. Stratton said.

The risk model was derived and tested based on data from 14,000 patients with no or mild nonproliferative retinopathy treated in the Gloucestershire area. The investigators looked at HbA_1c levels in the 12 months prior to diabetic eye screening to determine if they could predict which patients did and did not develop sight-threatening retinopathy. The risk model also considered the baseline retinopathy status in both eyes of patients; systolic and diastolic blood pressure; measures of kidney function and lipids; the time to develop retinopathy from diagnosis; and the type of diabetes.

“We found that the most important piece of information that went into the model was the grading at the baseline screening episode,” Dr. Stratton said. “So patients who had no retinopathy in either eye were at lowest risk, patients with background retinopathy in one eye had about a doubling of risk, and patients with background retinopathy in both eyes were at a much higher level of risk.”

The next most important parameters were the time since the first mention of a diagnosis of diabetes and HbA_1c in the year prior to screening. Total cholesterol in the year prior to screening also was a factor for consideration.

Hazard ratios for the development of diabetic retinopathy were 7.13 for patients with mild retinopathy in both eyes at baseline and 2.56 for those with mild retinopathy in one eye. The hazard ratios increased by 1.28 for every 10-mmol/mol increase in HbA_1c in the past 12 months, by 1.20 for every 5-year increase in the duration of diabetes, and by 1.12 for every 1-mmol/L increase in total serum cholesterol.

Three study populations, which altogether comprised almost 20,000 patients with diabetes, were used to validate the model; the largest population included more than 17,000 individuals. The main difference between the screening programs was the ethnic mix, Dr. Stratton highlighted. White patients dominated in the largest screening cohort, at 98%, but to a lesser extent in the other cohorts, at 47% (of 1,223 patients) and 81% (of 1,083). About half the patients in the cohorts were women, and the duration of diabetes ranged from 2.9 to 4.5 years. The majority (95%) of patients screened had type 1 diabetes. HbA_1c ranged from 6.3% to 8.2% overall.

The investigators stratified patients according to quintiles of risk using the model, and found that the quintiles correlated very well with the chances of patients developing sight-threatening eye disease in each of the three validation cohorts. Comparing the lowest- with the highest-risk quintiles, the rate of progression to sight-threatening retinopathy was 1-3 and 55-79 per 1,000 per patient-years, respectively. The overall event rate was around 20 per 1,000 patient years.

“Further validation in other screening programs and ethnic groups is required,” Dr. Stratton concluded.

The study was funded by a grant from the U.K. National Institute for Health Research, Health Technology Assessment Programme; and the Gloucestershire Hospitals National Health Service Foundation Trust. Dr. Stratton had no conflicts of interest.

VIENNA – A risk model based on a single assessment of hemoglobin A_1c and other parameters was able to differentiate well between patients who had a low and high risk for progression of sight-threatening diabetic retinopathy, researchers reported at the annual meeting of the European Association for the Study of Diabetes.

Although further validation is needed, the risk model “would be suitable for personalized screening intervals,” said presenting author Dr. Irene Stratton of the Gloucestershire (England) Hospitals NHS Foundation Trust. In England, the current recommendation is to screen everyone with diabetes annually using digital retinal photography.

Because of the increasing numbers of patients that require annual screening, health budgets for diabetic eye screening are being stretched and alternatives are desirable. In England, such screening considers both retinopathy and macropathology, Dr. Stratton said.

The risk model was derived and tested based on data from 14,000 patients with no or mild nonproliferative retinopathy treated in the Gloucestershire area. The investigators looked at HbA_1c levels in the 12 months prior to diabetic eye screening to determine if they could predict which patients did and did not develop sight-threatening retinopathy. The risk model also considered the baseline retinopathy status in both eyes of patients; systolic and diastolic blood pressure; measures of kidney function and lipids; the time to develop retinopathy from diagnosis; and the type of diabetes.

“We found that the most important piece of information that went into the model was the grading at the baseline screening episode,” Dr. Stratton said. “So patients who had no retinopathy in either eye were at lowest risk, patients with background retinopathy in one eye had about a doubling of risk, and patients with background retinopathy in both eyes were at a much higher level of risk.”

The next most important parameters were the time since the first mention of a diagnosis of diabetes and HbA_1c in the year prior to screening. Total cholesterol in the year prior to screening also was a factor for consideration.

Hazard ratios for the development of diabetic retinopathy were 7.13 for patients with mild retinopathy in both eyes at baseline and 2.56 for those with mild retinopathy in one eye. The hazard ratios increased by 1.28 for every 10-mmol/mol increase in HbA_1c in the past 12 months, by 1.20 for every 5-year increase in the duration of diabetes, and by 1.12 for every 1-mmol/L increase in total serum cholesterol.

Three study populations, which altogether comprised almost 20,000 patients with diabetes, were used to validate the model; the largest population included more than 17,000 individuals. The main difference between the screening programs was the ethnic mix, Dr. Stratton highlighted. White patients dominated in the largest screening cohort, at 98%, but to a lesser extent in the other cohorts, at 47% (of 1,223 patients) and 81% (of 1,083). About half the patients in the cohorts were women, and the duration of diabetes ranged from 2.9 to 4.5 years. The majority (95%) of patients screened had type 1 diabetes. HbA_1c ranged from 6.3% to 8.2% overall.

The investigators stratified patients according to quintiles of risk using the model, and found that the quintiles correlated very well with the chances of patients developing sight-threatening eye disease in each of the three validation cohorts. Comparing the lowest- with the highest-risk quintiles, the rate of progression to sight-threatening retinopathy was 1-3 and 55-79 per 1,000 per patient-years, respectively. The overall event rate was around 20 per 1,000 patient years.

“Further validation in other screening programs and ethnic groups is required,” Dr. Stratton concluded.

The study was funded by a grant from the U.K. National Institute for Health Research, Health Technology Assessment Programme; and the Gloucestershire Hospitals National Health Service Foundation Trust. Dr. Stratton had no conflicts of interest.