Treatment patterns of patients with HR+/HER2- metastatic breast cancer receiving CDK4/6 inhibitor-based regimens: a cohort study in the French nationwide healthcare database.

PURPOSE: To assess real-world treatment patterns in patients diagnosed with hormone receptor positive (HR+), human epidermal growth factor receptor 2 negative (HER2-) metastatic breast cancer (mBC) who received cyclin-dependent kinase 4/6 (CDK4/6) inhibitors in combination with an aromatase inhibitor (AI) or fulvestrant at first line. METHODS: Patient characteristics, treatment history, and outcomes data were extracted from the French 'Système National des Données de Santé' (SNDS) database for patients diagnosed with HR+/HER2- mBC between January 2014 and June 2019 and who received combination therapy with a CDK4/6 inhibitor and endocrine therapy. Kaplan-Meier methodology was used to assess time to next treatment (TTNT) and time to treatment discontinuation (TTTD). RESULTS: The cohort comprised 6061 patients including 4032 patients who received CDK4/6 inhibitors + AIs and 2029 patients who received CDK4/6 inhibitors + fulvestrant. Median follow-up was 13.5 months (IQR 9.5-18.1). The median TTTD of first line treatment with CDK4/6 inhibitors + AIs and CDK4/6 inhibitors + fulvestrant was 17.3 months (95% CI 16.8-17.9) and 9.7 months (95% CI 9.0-10.2), respectively. Chemotherapy was the most common second line therapy. Median TTTD of subsequent treatment lines was progressively shorter following first line treatment with CDK4/6 inhibitors + AIs (2nd line: 4.6 months (95% CI 4.4-4.9) and with CDK4/6 inhibitors + fulvestrant (2nd line: 4.7 months (95% CI 4.3-5.1). TTNT was longer than TTTD across lines of therapy. CONCLUSION: This real-world analysis confirms the effectiveness of CDK4/6 inhibitor-based regimens in French patients and highlights the frequent use of chemotherapy as second line therapy.

Association of a calcium channel blocker and diuretic prescribing cascade with adverse events: A population-based cohort study.

BACKGROUND: Prescribing cascades occur when a drug adverse event is misinterpreted as a new medical condition and a second, potentially unnecessary drug, is prescribed to treat the adverse event. The population-level consequences of prescribing cascades remain unknown. METHODS: This population-based cohort study used linked health administrative databases in Ontario, Canada. The study included community-dwelling adults, 66 years of age or older with hypertension and no history of heart failure (HF) or diuretic use in the prior year, newly dispensed a calcium channel blocker (CCB). Individuals subsequently dispensed a diuretic within 90 days of incident CCB dispensing were classified as the prescribing cascade group, and compared to those not dispensed a diuretic, classified as the non-prescribing cascade group. Those with and without a prescribing cascade were matched one-to-one on the propensity score and sex. The primary outcome was a serious adverse event (SAE), which was the composite of emergency room visits and hospitalizations in the 90-day follow-up period. We estimated hazard ratios (HRs) with 95% confidence intervals (CI) for SAE using an Andersen-Gill recurrent events regression model. RESULTS: Among 39,347 older adults with hypertension and no history of HF who were newly dispensed a CCB, 1881 (4.8%) had a new diuretic dispensed within 90 days after CCB initiation. Compared to the non-prescribing cascade group, those in the prescribing cascade group had higher rates of SAEs (HR: 1.21, 95% CI: 1.02-1.43). CONCLUSIONS: The CCB-diuretic prescribing cascade was associated with an increased rate of SAEs, suggesting harm beyond prescribing a second drug therapy. Our study raises awareness of the downstream impact of the CCB-diuretic prescribing cascade at a population level and provides an opportunity for clinicians who identify this prescribing cascade to review their patients' medications to determine if they can be optimized.

Remdesivir Is Associated With Reduced Mortality in COVID-19 Patients Requiring Supplemental Oxygen Including Invasive Mechanical Ventilation Across SARS-CoV-2 Variants.

Background: This comparative effectiveness study investigated the effect of remdesivir on in-hospital mortality among patients hospitalized for coronavirus disease 2019 (COVID-19) requiring supplemental oxygen including low-flow oxygen (LFO), high-flow oxygen/noninvasive ventilation (HFO/NIV), or invasive mechanical ventilation/extracorporeal membrane oxygenation (IMV/ECMO) across variant of concern (VOC) periods. Methods: Patients hospitalized for COVID-19 between December 2020 and April 2022 and administered remdesivir upon admission were 1:1 propensity score matched to patients not administered remdesivir during their COVID-19 hospitalization. Analyses were stratified by supplemental oxygen requirement upon admission and VOC period. Cox proportional hazards models were used to derive adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) for 14- and 28-day mortality. Results: Patients treated with remdesivir (67 582 LFO, 34 857 HFO/NIV, and 4164 IMV/ECMO) were matched to non-remdesivir patients. Unadjusted mortality rates were significantly lower for remdesivir-treated patients at 14 days (LFO: 6.4% vs. 8.8%; HFO/NIV: 16.8% vs. 19.4%; IMV/ECMO: 27.8% vs. 35.3%) and 28 days (LFO: 9.8% vs. 12.3%; HFO/NIV: 25.8% vs. 28.3%; IMV/ECMO: 41.4% vs. 50.6%). After adjustment, remdesivir treatment was associated with a statistically significant reduction in in-hospital mortality at 14 days (LFO: aHR, 0.72; 95% CI, 0.66-0.79; HFO/NIV: aHR, 0.83; 95% CI, 0.77-0.89; IMV/ECMO: aHR, 0.73; 95% CI, 0.65-0.82) and 28 days (LFO: aHR, 0.79; 95% CI, 0.73-0.85; HFO/NIV: aHR, 0.88; 95% CI, 0.82-0.93; IMV/ECMO: aHR, 0.74; 95% CI, 0.67-0.82) compared with non-remdesivir treatment. Lower risk of mortality among remdesivir-treated patients was observed across VOC periods. Conclusions: Remdesivir treatment is associated with significantly reduced mortality among patients hospitalized for COVID-19 requiring supplemental oxygen upon admission, including those requiring HFO/NIV or IMV/ECMO with severe or critical disease, across VOC periods.

Remdesivir Reduced Mortality in Immunocompromised Patients Hospitalized for COVID-19 Across Variant Waves: Findings From Routine Clinical Practice.

BACKGROUND: Immunocompromised patients are at high risk of severe coronavirus disease 2019 (COVID-19) and death, yet treatment strategies for immunocompromised patients hospitalized for COVID-19 reflect variations in clinical practice. In this comparative effectiveness study, we investigated the effect of remdesivir treatment on inpatient mortality among immunocompromised patients hospitalized for COVID-19 across all variants of concern (VOC) periods. METHODS: Data for immunocompromised patients hospitalized for COVID-19 between December 2020 and April 2022 were extracted from the US PINC AITM Healthcare Database. Patients who received remdesivir within 2 days of hospitalization were matched 1:1 using propensity score matching to patients who did not receive remdesivir. Additional matching criteria included admission month, age group, and hospital. Cox proportional hazards models were used to examine the effect of remdesivir on risk of 14- and 28-day mortality during VOC periods. RESULTS: A total of 19 184 remdesivir patients were matched to 11 213 non-remdesivir patients. Overall, 11.1% and 17.7% of remdesivir patients died within 14 and 28 days, respectively, compared with 15.4% and 22.4% of non-remdesivir patients. Remdesivir was associated with a reduction in mortality at 14 (hazard ratio [HR], 0.70; 95% confidence interval, .62-.78) and 28 days (HR, 0.75; 95% CI, .68-.83). The survival benefit remained significant during the pre-Delta, Delta, and Omicron periods. CONCLUSIONS: Prompt initiation of remdesivir in immunocompromised patients hospitalized for COVID-19 is associated with significant survival benefit across all variant waves. These findings provide much-needed evidence relating to the effectiveness of a foundational treatment for hospitalized COVID-19 patients among a high-risk population.

The association between immigration status and the development of type 2 diabetes in women with a prior diagnosis of gestational diabetes: A population-based study.

AIMS: The aim of this study was to examine the influence of immigration status and region of origin on the risk of type 2 diabetes in women with prior gestational diabetes (GDM). METHODS: This retrospective population-based cohort study included women with gestational diabetes (GDM) aged 16 to 50 years in Ontario, Canada, who gave birth between 2006 and 2014. We compared the incidence of type 2 diabetes after delivery between long-term residents and immigrants-overall, by time since immigration and by region of-using Cox regression adjusted for age, year, neighbourhood income, rurality, infant birth weight and presence of hypertensive disorders of pregnancy (HDP). RESULTS: Among 38,515 women with prior GDM (42% immigrants), immigrants had a significantly higher risk of type 2 diabetes compared with long-term residents (adjusted hazard ratio [HR] 1.19, 95% confidence interval [CI] 1.13-1.26), with no meaningful difference based on time since immigration. The highest adjusted relative risks of type 2 diabetes compared with long-term residents were found for immigrants from Sub-Saharan Africa (HR 1.63, 95% CI 1.40-1.90), Latin America/Caribbean (HR 1.44, 95% CI 1.28-1.62) and South Asia (HR 1.34, 95% CI 1.25-1.44). CONCLUSIONS: Immigration is associated with a significantly higher risk of type 2 diabetes after GDM, particularly for women from certain low- and middle-income countries. Diabetes prevention strategies will need to consider the unique needs of immigrants from these regions.

External control arms for rare diseases: building a body of supporting evidence.

Comparator arms in randomized clinical trials may be impractical and/or unethical to assemble in rare diseases. In the absence of comparator arms, evidence generated from external control studies has been used to support successful regulatory submissions and health technology assessments (HTA). However, conducting robust and rigorous external control arm studies is challenging and despite all efforts, residual biases may remain. As a result, regulatory and HTA agencies may request additional external control analyses so that decisions may be made based upon a body of supporting evidence.This paper introduces external control studies and provides an overview of the key methodological issues to be considered in the design of these studies. A series of case studies are presented in which evidence derived from one or more external controls was submitted to regulatory and HTA agencies to provide support for the consistency of findings.

The association between offspring birthweight and future risk of maternal diabetes: A population-based study.

AIMS: As an indicator of maternal cardiometabolic health, newborn birthweight may be an important predictor of maternal type 2 diabetes mellitus (diabetes). We evaluated the relation between offspring birthweight and onset of maternal diabetes after pregnancy. METHODS: This retrospective cohort study used linked population-based health databases from Ontario, Canada. We included women aged 16-50 years without pre-pregnancy diabetes, and who had a live birth between 2006 and 2014. We used Cox proportional hazard regression to evaluate the association between age- and sex-standardized offspring birthweight percentile categories and incident maternal diabetes, while adjusting for maternal age, parity, year, ethnicity, gestational diabetes (GDM) and hypertensive disorders of pregnancy (HDP). Results were further stratified by the presence of GDM in the index pregnancy. RESULTS: Of 893,777 eligible participants, 14,329 (1.6%) women were diagnosed with diabetes over a median (IQR) of 4.4 (1.5-7.4) years of follow-up. There was a continuous positive relation between newborn birthweight above the 75th percentile and maternal diabetes. Relative to a birthweight between the 50th and 74.9th percentiles, women whose newborn had a birthweight between the 97th and 100th percentiles had an adjusted hazards ratio (aHR) of diabetes of 2.30 (95% CI 2.16-2.46), including an aHR of 2.01 (95% CI 1.83-2.21) among those with GDM, and 2.59 (2.36-2.84) in those without GDM. CONCLUSIONS: A higher offspring birthweight signals an increased risk of maternal diabetes, offering another potentially useful way to identify women especially predisposed to diabetes.

Estimating individual lifetime risk of incident cardiovascular events in adults with Type 2 diabetes: an update and geographical calibration of the DIAbetes Lifetime perspective model (DIAL2).

AIMS: The 2021 European Society of Cardiology cardiovascular disease (CVD) prevention guidelines recommend the use of (lifetime) risk prediction models to aid decisions regarding intensified preventive treatment options in adults with Type 2 diabetes, e.g. the DIAbetes Lifetime perspective model (DIAL model). The aim of this study was to update the DIAL model using contemporary and representative registry data (DIAL2) and to systematically calibrate the model for use in other European countries. METHODS AND RESULTS: The DIAL2 model was derived in 467 856 people with Type 2 diabetes without a history of CVD from the Swedish National Diabetes Register, with a median follow-up of 7.3 years (interquartile range: 4.0-10.6 years) and comprising 63 824 CVD (including fatal CVD, non-fatal stroke and non-fatal myocardial infarction) events and 66 048 non-CVD mortality events. The model was systematically recalibrated to Europe's low- and moderate-risk regions using contemporary incidence data and mean risk factor distributions. The recalibrated DIAL2 model was externally validated in 218 267 individuals with Type 2 diabetes from the Scottish Care Information-Diabetes (SCID) and Clinical Practice Research Datalink (CPRD). In these individuals, 43 074 CVD events and 27 115 non-CVD fatal events were observed. The DIAL2 model discriminated well, with C-indices of 0.732 [95% confidence interval (CI) 0.726-0.739] in CPRD and 0.700 (95% CI 0.691-0.709) in SCID. CONCLUSION: The recalibrated DIAL2 model provides a useful tool for the prediction of CVD-free life expectancy and lifetime CVD risk for people with Type 2 diabetes without previous CVD in the European low- and moderate-risk regions. These long-term individualized measures of CVD risk are well suited for shared decision-making in clinical practice as recommended by the 2021 CVD ESC prevention guidelines.

Development and Validation of a Lifetime Risk Model for Kidney Failure and Treatment Benefit in Type 2 Diabetes: 10-Year and Lifetime Risk Prediction Models.

BACKGROUND AND OBJECTIVES: Individuals with type 2 diabetes are at a higher risk of developing kidney failure. The objective of this study was to develop and validate a decision support tool for estimating 10-year and lifetime risks of kidney failure in individuals with type 2 diabetes as well as estimating individual treatment effects of preventive medication. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: The prediction algorithm was developed in 707,077 individuals with prevalent and incident type 2 diabetes from the Swedish National Diabetes Register for 2002-2019. Two Cox proportional regression functions for kidney failure (first occurrence of kidney transplantation, long-term dialysis, or persistent eGFR <15 ml/min per 1.73 m2) and all-cause mortality as respective end points were developed using routinely available predictors. These functions were combined into life tables to calculate the predicted survival without kidney failure while using all-cause mortality as the competing outcome. The model was externally validated in 256,265 individuals with incident type 2 diabetes from the Scottish Care Information Diabetes database between 2004 and 2019. RESULTS: During a median follow-up of 6.8 years (interquartile range, 3.2-10.6), 8004 (1%) individuals with type 2 diabetes in the Swedish National Diabetes Register cohort developed kidney failure, and 202,078 (29%) died. The model performed well, with c statistics for kidney failure of 0.89 (95% confidence interval, 0.88 to 0.90) for internal validation and 0.74 (95% confidence interval, 0.73 to 0.76) for external validation. Calibration plots showed good agreement in observed versus predicted 10-year risk of kidney failure for both internal and external validation. CONCLUSIONS: This study derived and externally validated a prediction tool for estimating 10-year and lifetime risks of kidney failure as well as life years free of kidney failure gained with preventive treatment in individuals with type 2 diabetes using easily available clinical predictors. PODCAST: This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast/CJASN/2022_11_04_CJN05020422.mp3.

Mortality trends in type 1 diabetes: a multicountry analysis of six population-based cohorts.

AIMS/HYPOTHESIS: Mortality has declined in people with type 1 diabetes in recent decades. We examined how the pattern of decline differs by country, age and sex, and how mortality trends in type 1 diabetes relate to trends in general population mortality. METHODS: We assembled aggregate data on all-cause mortality during the period 2000-2016 in people with type 1 diabetes aged 0-79 years from Australia, Denmark, Latvia, Scotland, Spain (Catalonia) and the USA (Kaiser Permanente Northwest). Data were obtained from administrative sources, health insurance records and registries. All-cause mortality rates in people with type 1 diabetes, and standardised mortality ratios (SMRs) comparing type 1 diabetes with the non-diabetic population, were modelled using Poisson regression, with age and calendar time as quantitative variables, describing the effects using restricted cubic splines with six knots for age and calendar time. Mortality rates were standardised to the age distribution of the aggregate population with type 1 diabetes. RESULTS: All six data sources showed a decline in age- and sex-standardised all-cause mortality rates in people with type 1 diabetes from 2000 to 2016 (or a subset thereof), with annual changes in mortality rates ranging from -2.1% (95% CI -2.8%, -1.3%) to -5.8% (95% CI -6.5%, -5.1%). All-cause mortality was higher for male individuals and for older individuals, but the rate of decline in mortality was generally unaffected by sex or age. SMR was higher in female individuals than male individuals, and appeared to peak at ages 40-70 years. SMR declined over time in Denmark, Scotland and Spain, while remaining stable in the other three data sources. CONCLUSIONS/INTERPRETATION: All-cause mortality in people with type 1 diabetes has declined in recent years in most included populations, but improvements in mortality relative to the non-diabetic population are less consistent.

Trends in all-cause mortality among people with diagnosed diabetes in high-income settings: a multicountry analysis of aggregate data.

BACKGROUND: Population-level trends in mortality among people with diabetes are inadequately described. We aimed to examine the magnitude and trends in excess all-cause mortality in people with diabetes. METHODS: In this retrospective, multicountry analysis, we collected aggregate data from 19 data sources in 16 high-income countries or jurisdictions (in six data sources in Asia, eight in Europe, one from Australia, and four from North America) for the period from Jan 1, 1995, to Dec 31, 2016, (or a subset of this period) on all-cause mortality in people with diagnosed total or type 2 diabetes. We collected data from administrative sources, health insurance records, registries, and a health survey. We estimated excess mortality using the standardised mortality ratio (SMR). FINDINGS: In our dataset, there were approximately 21 million deaths during 0·5 billion person-years of follow-up among people with diagnosed diabetes. 17 of 19 data sources showed decreases in the age-standardised and sex-standardised mortality in people with diabetes, among which the annual percentage change in mortality ranged from -0·5% (95% CI -0·7 to -0·3) in Hungary to -4·2% (-4·3 to -4·1) in Hong Kong. The largest decreases in mortality were observed in east and southeast Asia, with a change of -4·2% (95% CI -4·3 to -4·1) in Hong Kong, -4·0% (-4·8 to -3·2) in South Korea, -3·5% (-4·0 to -3·0) in Taiwan, and -3·6% (-4·2 to -2·9) in Singapore. The annual estimated change in SMR between people with and without diabetes ranged from -3·0% (95% CI -3·0 to -2·9; US Medicare) to 1·6% (1·4 to 1·7; Lombardy, Italy). Among the 17 data sources with decreasing mortality among people with diabetes, we found a significant SMR increase in five data sources, no significant SMR change in four data sources, and a significant SMR decrease in eight data sources. INTERPRETATION: All-cause mortality in diabetes has decreased in most of the high-income countries we assessed. In eight of 19 data sources analysed, mortality decreased more rapidly in people with diabetes than in those without diabetes. Further longevity gains will require continued improvement in prevention and management of diabetes. FUNDING: US Centers for Disease Control and Prevention, Diabetes Australia Research Program, and Victoria State Government Operational Infrastructure Support Program.

Population median imputation was noninferior to complex approaches for imputing missing values in cardiovascular prediction models in clinical practice.

OBJECTIVES: To compare the validity and robustness of five methods for handling missing characteristics when using cardiovascular disease risk prediction models for individual patients in a real-world clinical setting. STUDY DESIGN AND SETTING: The performance of the missing data methods was assessed using data from the Swedish National Diabetes Registry (n = 419,533) with external validation using the Scottish Care Information - diabetes database (n = 226,953). Five methods for handling missing data were compared. Two methods using submodels for each combination of available data, two imputation methods: conditional imputation and median imputation, and one alternative modeling method, called the naïve approach, based on hazard ratios and populations statistics of known risk factors only. The validity was compared using calibration plots and c-statistics. RESULTS: C-statistics were similar across methods in both development and validation data sets, that is, 0.82 (95% CI 0.82-0.83) in the Swedish National Diabetes Registry and 0.74 (95% CI 0.74-0.75) in Scottish Care Information-diabetes database. Differences were only observed after random introduction of missing data in the most important predictor variable (i.e., age). CONCLUSION: Validity and robustness of median imputation was not dissimilar to more complex methods for handling missing values, provided that the most important predictor variables, such as age, are not missing.

Development and validation of a cardiovascular risk prediction model in type 1 diabetes.

AIMS/HYPOTHESIS: We aimed to report current rates of CVD in type 1 diabetes and to develop a CVD risk prediction tool for type 1 diabetes. METHODS: A cohort of 27,527 people with type 1 diabetes without prior CVD was derived from the national register in Scotland. Incident CVD events during 199,552 person-years of follow-up were ascertained using hospital admissions and death registers. A Poisson regression model of CVD was developed and then validated in the Swedish National Diabetes Register (n = 33,183). We compared the percentage with a high 10 year CVD risk (i.e., ≥10%) using the model with the percentage eligible for statins using current guidelines by age. RESULTS: The age-standardised rate of CVD per 100,000 person-years was 4070 and 3429 in men and women, respectively, with type 1 diabetes in Scotland, and 4014 and 3956 in men and women in Sweden. The final model was well calibrated (Hosmer-Lemeshow test p > 0.05) and included a further 22 terms over a base model of age, sex and diabetes duration (C statistic 0.82; 95% CI 0.81, 0.83). The model increased the base model C statistic from 0.66 to 0.80, from 0.60 to 0.75 and from 0.62 to 0.68 in those aged <40, 40-59 and ≥ 60 years, respectively (all p values <0.005). The model required minimal calibration in Sweden and had a C statistic of 0.85. Under current guidelines, >90% of those aged 20-39 years and 100% of those ≥40 years with type 1 diabetes were eligible for statins, but it was not until age 65 upwards that 100% had a modelled risk of CVD ≥10% in 10 years. CONCLUSIONS/INTERPRETATION: A prediction tool such as that developed here can provide individualised risk predictions. This 10 year CVD risk prediction tool could facilitate patient discussions regarding appropriate statin prescribing. Apart from 10 year risk, such discussions may also consider longer-term CVD risk, the potential for greater benefits from early vs later statin intervention, the potential impact on quality of life of an early CVD event and evidence on safety, all of which could influence treatment decisions, particularly in younger people with type 1 diabetes.

Evidence of a gabapentinoid and diuretic prescribing cascade among older adults with lower back pain.

BACKGROUND/OBJECTIVES: Gabapentinoids are commonly prescribed to relieve pain. The development of edema, an established adverse effect of gabapentinoids, may lead to a potentially harmful prescribing cascade whereby individuals are subsequently prescribed diuretics and exposed to diuretic-induced adverse events. The frequency of this prescribing cascade is unknown. Our objective was to measure the association between new dispensing of a gabapentinoid and the subsequent dispensing of a diuretic in older adults with new low back pain. DESIGN: Population-based cohort study. SETTING: Ontario, Canada. PARTICIPANTS: A total of 260,344 community-dwelling adults aged 66 years or older, newly diagnosed with low back pain between April 1, 2011, and March 31, 2019. MEASUREMENTS: Exposure status was assigned using dispensed medications in the 1 week after low back pain diagnosis. Older adults newly dispensed a gabapentinoid (N = 7867) were compared with older adults who were not newly dispensed a gabapentinoid (N = 252,477). Hazard ratios (HRs) with 95% confidence intervals (CIs) for dispensing of a diuretic within 90 days of follow-up among older adults prescribed gabapentin relative to those who were not. RESULTS: Older adults newly dispensed a gabapentinoid had a higher risk of being subsequently dispensed a diuretic within 90 days compared with older adults who were not prescribed a gabapentinoid (2.0% vs. 1.3%). After covariate adjustment, new gabapentinoid users had a higher rate of being dispensed a diuretic compared with those not prescribed a gabapentinoid (HR: 1.44, 95% CI: 1.23, 1.70). The rate of diuretic prescription among new gabapentinoid users increased with increasing gabapentinoid dosages. CONCLUSIONS: We have demonstrated the presence of a potentially inappropriate and harmful prescribing cascade. Given the widespread use of gabapentinoids, the population-based scale of this problem may be substantial. Increased awareness of this prescribing cascade is required to reduce the unnecessary use of diuretics and the exposure of patients to additional adverse drug events.

Diabetes after pregnancy: a study protocol for the derivation and validation of a risk prediction model for 5-year risk of diabetes following pregnancy.

BACKGROUND: Pregnancy offers a unique opportunity to identify women at higher future risk of type 2 diabetes mellitus (DM). In pregnancy, a woman has greater engagement with the healthcare system, and certain conditions are more apt to manifest, such as gestational DM (GDM) that are important markers for future DM risk. This study protocol describes the development and validation of a risk prediction model (RPM) for estimating a woman's 5-year risk of developing type 2 DM after pregnancy. METHODS: Data will be obtained from existing Ontario population-based administrative datasets. The derivation cohort will consist of all women who gave birth in Ontario, Canada between April 2006 and March 2014. Pre-specified predictors will include socio-demographic factors (age at delivery, ethnicity), maternal clinical factors (e.g., body mass index), pregnancy-related events (gestational DM, hypertensive disorders of pregnancy), and newborn factors (birthweight percentile). Incident type 2 DM will be identified by linkage to the Ontario Diabetes Database. Weibull accelerated failure time models will be developed to predict 5-year risk of type 2 DM. Measures of predictive accuracy (Nagelkerke's R2), discrimination (C-statistics), and calibration plots will be generated. Internal validation will be conducted using a bootstrapping approach in 500 samples with replacement, and an optimism-corrected C-statistic will be calculated. External validation of the RPM will be conducted by applying the model in a large population-based pregnancy cohort in Alberta, and estimating the above measures of model performance. The model will be re-calibrated by adjusting baseline hazards and coefficients where appropriate. DISCUSSION: The derived RPM may help identify women at high risk of developing DM in a 5-year period after pregnancy, thus facilitate lifestyle changes for women at higher risk, as well as more frequent screening for type 2 DM after pregnancy.

Trends in the incidence of diagnosed diabetes: a multicountry analysis of aggregate data from 22 million diagnoses in high-income and middle-income settings.

BACKGROUND: Diabetes prevalence is increasing in most places in the world, but prevalence is affected by both risk of developing diabetes and survival of those with diabetes. Diabetes incidence is a better metric to understand the trends in population risk of diabetes. Using a multicountry analysis, we aimed to ascertain whether the incidence of clinically diagnosed diabetes has changed over time. METHODS: In this multicountry data analysis, we assembled aggregated data describing trends in diagnosed total or type 2 diabetes incidence from 24 population-based data sources in 21 countries or jurisdictions. Data were from administrative sources, health insurance records, registries, and a health survey. We modelled incidence rates with Poisson regression, using age and calendar time (1995-2018) as variables, describing the effects with restricted cubic splines with six knots for age and calendar time. FINDINGS: Our data included about 22 million diabetes diagnoses from 5 billion person-years of follow-up. Data were from 19 high-income and two middle-income countries or jurisdictions. 23 data sources had data from 2010 onwards, among which 19 had a downward or stable trend, with an annual estimated change in incidence ranging from -1·1% to -10·8%. Among the four data sources with an increasing trend from 2010 onwards, the annual estimated change ranged from 0·9% to 5·6%. The findings were robust to sensitivity analyses excluding data sources in which the data quality was lower and were consistent in analyses stratified by different diabetes definitions. INTERPRETATION: The incidence of diagnosed diabetes is stabilising or declining in many high-income countries. The reasons for the declines in the incidence of diagnosed diabetes warrant further investigation with appropriate data sources. FUNDING: US Centers for Disease Control and Prevention, Diabetes Australia Research Program, and Victoria State Government Operational Infrastructure Support Program.

BMI and risk of gestational diabetes among women of South Asian and Chinese ethnicity: a population-based study.

AIMS/HYPOTHESIS: The aim of this study was to examine how BMI influences the association between Asian ethnicity and risk of gestational diabetes (GDM). METHODS: This population-based cohort study included pregnant women without pre-existing diabetes mellitus in Ontario, Canada between 2012 and 2014. Women of Chinese and South Asian ethnicity were identified using a validated surname algorithm. GDM was ascertained using hospitalisation codes. The relationship between ethnicity and GDM was modelled using modified Poisson regression, adjusted for maternal age, pre-pregnancy BMI, parity, previous GDM, long-term residency status, income quintile and smoking status. An interaction term between ethnicity and pre-pregnancy BMI was tested. RESULTS: Of 231,618 pregnant women, 9289 (4.0%) were of South Asian ethnicity and 12,240 (5.3%) were of Chinese ethnicity. Relative to women from the general population, in whom prevalence of GDM was 4.3%, the adjusted RR of GDM was higher among those of South Asian ethnicity (1.81 [95% CI 1.64, 1.99]) and Chinese ethnicity (1.66 [95% CI 1.53, 1.80]). The association between GDM and Asian ethnicity remained significant across BMI categories but differed according to BMI. The prevalence of GDM exceeded 5% at an estimated BMI of 21.5 kg/m2 among South Asian women, 23.0 kg/m2 among Chinese women and 29.5 kg/m2 among the general population. CONCLUSIONS/INTERPRETATION: The risk of GDM is significantly higher in South Asian and Chinese women, whose BMI is lower than that of women in the general population. Accordingly, targeted GDM prevention strategies may need to consider lower BMI cut-points for Asian populations.

Risk Factor Control and Cardiovascular Event Risk in People With Type 2 Diabetes in Primary and Secondary Prevention Settings.

BACKGROUND: To examine the association between the degree of risk factor control and cardiovascular disease (CVD) risk in type 2 diabetes and to assess if the presence of cardio-renal disease modifies these relationships. METHODS: A retrospective cohort study using data from English practices from CPRD GOLD (Clinical Practice Research Datalink) and the SCI-Diabetes dataset (Scottish Care Information-Diabetes), with linkage to hospital and mortality data. We identified 101 749 with type 2 diabetes (T2D) in CPRD matched with 378 938 controls without diabetes and 330 892 with type 2 diabetes in SCI-Diabetes between 2006 and 2015. The main exposure was number of optimized risk factors: nonsmoker, total cholesterol ≤4 mmol/L, triglycerides ≤1.7 mmol/L, glycated haemoglobin (HbA1c) ≤53 mmol/mol (≤7.0%), systolic blood pressure <140mm Hg, or <130 mm Hg if high risk. Cox models were used to assess cardiovascular risk associated with levels of risk factor control. RESULTS: In CPRD, the mean baseline age in T2D was 63 years and 28% had cardio-renal disease (SCI-Diabetes: 62 years; 35% cardio-renal disease). Over 3 years follow-up (SCI-Diabetes: 6 years), CVD events occurred among 27 900 (27%) CPRD-T2D, 101 362 (31%) SCI-Diabetes-T2D, and 75 520 (19%) CPRD-controls. In CPRD, compared with controls, T2D participants with optimal risk factor control (all risk factors controlled) had a higher risk of CVD events (adjusted hazard ratio, 1.21; 95% confidence interval, 1.12-1.29). In T2D participants from CPRD and SCI-Diabetes, pooled hazard ratios for CVD associated with 5 risk factors being elevated versus optimal risk factor control were 1.09 (95% confidence interval, 1.01-1.17) in people with cardio-renal disease but 1.96 (95% confidence interval, 1.82-2.12) in people without cardio-renal disease. People without cardio-renal disease were younger and more likely to have likely to have suboptimal risk factor control but had fewer prescriptions for risk factor modifying medications than those with cardio-renal disease. CONCLUSIONS: Optimally managed people with T2D have a 21% higher CVD risk when compared with controls. People with T2D without cardio-renal disease would be predicted to benefit greatly from CVD risk factor intervention.