Modelling cumulative exposure for inference about drug effects in observational studies

Drug Exposure As a Predictor in Diabetic Retinopathy Risk Prediction Models-A Systematic Review and Meta-Analysis

PURPOSE

To conduct a systematic review to assess drug exposure handling in diabetic retinopathy (DR) risk prediction models, a network-meta-analysis to identify drugs associated with DR and a meta-analysis to determine which drugs contributed to enhanced model performance.

DESIGN

Systematic review and meta-analysis.

METHODS

We included studies presenting DR models incorporating drug exposure as a predictor. We searched EMBASE, MEDLINE, and SCOPUS from inception to December 2023. We evaluated the quality of studies using the Prediction model Risk of Bias Assessment Tool and certainty using GRADE. We conducted network meta-analysis and meta-analysis to estimate the odds ratio (OR) and pooled C-statistic, respectively, and 95% confidence intervals (CI) (PROSPERO: CRD42022349764).

RESULTS

Of 5,653 records identified, we included 28 studies of 678,837 type 1 or 2 diabetes participants, of which 38,579 (5.7%) had DR. A total of 19, 3, and 7 studies were at high, unclear, and low risk of bias, respectively. Drugs included in models as predictors were: insulin (n = 24), antihypertensives (n = 5), oral antidiabetics (n = 12), lipid-lowering drugs (n = 7), antiplatelets (n = 2). Drug exposure was modelled primarily as a categorical variable (n = 23 studies). Two studies handled drug exposure as time-varying covariates, and one as a time-dependent covariate. Insulin was associated with an increased risk of DR (OR = 2.50; 95% CI: 1.61-3.86). Models that included insulin (n = 9) had a higher pooled C-statistic (C-statistic = 0.84, CI: 0.80-0.88), compared to models (n = 9) that incorporated a combination of drugs alongside insulin (C-statistic = 0.79, CI: 0.74-0.84), as well as models (n = 3) not including insulin (C-statistic = 0.70, CI: 0.64-0.75). Limitations include the high risk of bias and significant heterogeneity in reviewed studies.

CONCLUSION

This is the first review assessing drug exposure handling in DR prediction models. Drug exposure was primarily modelled as a categorical variable, with insulin associated with improved model performance. However, due to suboptimal drug handling, associations between other drugs and model performance may have been overlooked. This review proposes the following for future DR prediction models: (1) evaluation of drug exposure as a variable, (2) use of time-varying methodologies, and (3) consideration of drug regimen details. Improving drug exposure handling could potentially unveil novel variables capable of significantly enhancing the predictive capability of prediction models.

Association between antihypertensive medications and risk of skin cancer in people older than 65 years: a population-based study

BACKGROUND:

The risk of skin cancer associated with antihypertensive medication use is unclear, although thiazides have been implicated in regulatory safety warnings. We aimed to assess whether use of thiazides and other antihypertensives is associated with increased rates of keratinocyte carcinoma and melanoma.

METHODS:

We conducted a population-based inception cohort study using linked administrative health data from Ontario, 1998–2017. We matched adults aged ≥ 66 years with a first prescription for an antihypertensive medication (thiazides, angiotensin-converting enzyme inhibitors, angiotensin II receptor blockers, calcium channel blockers, β-blockers) by age and sex to 2 unexposed adults who were prescribed a non-antihypertensive medication within 30 days of the index date. We evaluated each antihypertensive class in a separate cohort study. Our primary exposure was the cumulative dose within each class, standardized according to the World Health Organization’s Defined Daily Dose. Outcomes were time to first keratinocyte carcinoma, advanced keratinocyte carcinoma and melanoma.

RESULTS:

The inception cohorts included a total of 302 634 adults prescribed an antihypertensive medication and 605 268 unexposed adults. Increasing thiazide exposure was associated with an increased rate of incident keratinocyte carcinoma (adjusted hazard ratios [HRs] per 1 Defined Annual Dose unit 1.08, 95% confidence interval [CI] 1.03–1.14), advanced keratinocyte carcinoma (adjusted HR 1.07, 95% CI 0.93–1.23) and melanoma (adjusted HR 1.34, 95% CI 1.01–1.78). We found no consistent evidence of association between other antihypertensive classes and keratinocyte carcinoma or melanoma.

INTERPRETATION:

Higher cumulative exposure to thiazides was associated with increased rates of incident skin cancer in people aged 66 years and older. Consideration of other antihypertensive treatments in patients at high risk of skin cancer may be warranted.

Impact of time-varying cumulative bevacizumab exposures on survival: re-analysis of data from randomized clinical trial in patients with metastatic colo-rectal cancer

Background

As cancer treatment, biotherapies can be as effective as chemotherapy while reducing the risk of secondary effects, so that they can be taken over longer periods than conventional chemotherapy. Thus, some trials aimed at assessing the benefit of maintaining biotherapies during chemotherapy-free intervals (CFI). For example, the recent PRODIGE9 trial assessed the effect of maintaining bevacizumab during CFI in metastatic colorectal cancer (mCRC) patients. However, its analysis was hindered by a small difference of exposure to the treatment between the randomized groups and by a large proportion of early drop outs, leading to a potentially unbalanced distribution of confounding factors among the trial completers. To address these limitations, we re-analyzed the PRODIGE9 data to assess the effects of different exposure metrics on all-cause mortality of patients with mCRC using methods originally developed for observational studies.

Methods

To account for the actual patterns of drug use by individual patients and for possible cumulative effects, we used five alternative time-varying exposure metrics: (i) cumulative dose, (ii) quantiles of the cumulative dose, (iii) standardized cumulative dose, (iv) Theoretical Blood Concentration (TBC), and (v) Weighted Cumulative Exposure (WCE). The last two metrics account for the timing of drug use. Treatment effects were estimated using adjusted Hazard Ratio from multivariable Cox proportional hazards models.

Results

After excluding 112 patients who died during the induction period, we analyzed data on 382 patients, among whom 320 (83.8%) died. All time-varying exposures improved substantially the model’s fit to data, relative to using only the time-invariant randomization group. All exposures indicated a protective effect for higher cumulative bevacizumab doses. The best-fitting WCE and TBC models accounted for both the cumulative effects and the different impact of doses taken at different times.

Conclusions

All time-varying analyses, regardless of the exposure metric used, consistently suggested protective effects of higher cumulative bevacizumab doses. However, the results may partly reflect the presence of a confusion bias. Complementing the main ITT analysis of maintenance trials with an analysis of potential cumulative effects of treatment actually taken can provide new insights, but the results must be interpreted with caution because they do not benefit from the randomization.

Trial registration

clinicaltrials.gov, NCT00952029. Registered 8 August 2009.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-020-01202-9.

Is Gliclazide Associated with a Lower Obesity-Related Cancer Risk Compared to Other Sulfonylureas? A Long-term Prospective Cohort Study

BACKGROUND

Gliclazide has been suspected to be associated with a lower obesity-related cancer risk; however, current evidence is limited by important methodologic shortcomings. This study aimed to evaluate whether gliclazide is preferred over other sulfonylureas regarding obesity-related cancer risk.

METHODS

In this prospective cohort study, an annual benchmarking database in Dutch primary care (Zwolle Outpatient Diabetes project Integrating Available CareZODIAC, 1998-2014) was linked to the Netherlands Cancer Registry and the Dutch Personal Record Database. Of the 71,648 patients with type 2 diabetes, we included 26,207 who used sulfonylureas and had no history of cancer or insulin use at baseline. Obesity-related cancer was defined using the latest definition of the World Cancer Research Fund. Cox regression analyses were used to estimate HRs, with both baseline sulfonylurea and cumulative exposure modeled and corrected for baseline covariates.

RESULTS

During follow-up for 167,692 person-years, there were 1,111 obesity-related cancer events. For males, the adjusted HRs [95% confidence interval (CI)] for baseline sulfonylurea compared with gliclazide were as follows: glibenclamide, 1.10 (0.92-2.69); glimepiride, 1.13 (0.68-1.84); and tolbutamide, 0.93 (0.59-1.48). For females, these were as follows: glibenclamide, 1.49 (0.72-3.13); glimepiride, 0.96 (0.59-1.54); and tolbutamide, 0.84 (0.54-1.28). The adjusted HRs (95% CI) for one more year of cumulative exposure compared with gliclazide were as follows: glibenclamide, 0.90 (0.71-1.14); glimepiride, 0.96 (0.87-1.06); and tolbutamide, 1.00 (0.92-1.09). For females, these were as follows: glibenclamide, 0.93 (0.77-1.13); glimepiride, 0.99 (0.90-1.10); and tolbutamide, 1.04 (0.96-1.13).

CONCLUSIONS

Obesity-related cancer risk was comparable between gliclazide and other sulfonylureas.

IMPACT

Gliclazide is not preferred over other sulfonylureas regarding obesity-related cancer risk.

Pharmacoepidemiology: Using randomised control trials and observational studies in clinical decision-making

Weighing up sources of evidence is a key skill for clinical decision-makers. Randomised controlled trials (RCTs) and observational studies each have advantages and disadvantages, and in both cases perceived weaknesses can be improved through modifications of design and analysis. In the field of pharmacoepidemiology, RCTs are the best way to determine whether an intervention modifies an outcome being studied, largely because randomisation reduces bias and confounding. Observational studies are useful to investigate whether benefits/harms of a treatment are seen in day-to-day clinical practice in a wider group of patients. Although observational studies, even in a small cohort, can provide very useful clinical evidence, they may also be misleading (as shown by subsequent RCTs), in part because of allocation bias. There is an unmet need for clinicians to become well versed in appraising the study design and statistical analysis of observational pharmacoepidemiology (OP) studies, rather like the medical training already offered for RCT evaluation. This is because OP studies are likely to become more common with the computerisation of healthcare records and increasingly contribute to the evidence base available for clinical decision-making. However, when the results of an RCT conflict with the results of an OP study, the findings of the RCT should be preferred, especially if its findings have been repeated elsewhere. Conversely, OP studies that align with the findings of RCTs can provide rich and useful information to complement that generated by RCTs.

The effect of dapagliflozin on glycaemic control and other cardiovascular disease risk factors in type 2 diabetes mellitus: a real-world observational study

AIMS/HYPOTHESIS

Dapagliflozin, a sodium-glucose cotransporter 2 (SGLT2) inhibitor, is indicated for improving glycaemic control in type 2 diabetes mellitus. Whether its effects on HbA_1c and other variables, including safety outcomes, in clinical trials are obtained in real-world practice needs to be established.

METHODS

We used data from the comprehensive national diabetes register, the Scottish Care Information-Diabetes (SCI-Diabetes) collaboration database, available from 2004 to mid-2016. Data within this database were linked to mortality data from the General Registrar, available from the Information Services Division (ISD) of the National Health Service in Scotland. We calculated crude within-person differences between pre- and post-drug-initiation values of HbA_1c, BMI, body weight, systolic blood pressure (SBP) and eGFR. We used mixed-effects regression models to adjust for within-person time trajectories in these measures. For completeness, we evaluated safety outcomes, cardiovascular disease events, lower-limb amputation and diabetic ketoacidosis, focusing on cumulative exposure effects, using Cox proportional hazard models, though power to detect such effects was limited.

RESULTS

Among 8566 people exposed to dapagliflozin over a median of 210 days the crude within-person change in HbA_1c was -10.41 mmol/mol (-0.95%) after 3 months' exposure. The crude change after 12 months was -12.99 mmol/mol (-1.19%) but considering the expected rise over time in HbA_1c gave a dapagliflozin-exposure-effect estimate of -15.14 mmol/mol (95% CI -15.87, -14.41) (-1.39% [95% CI -1.45, -1.32]) at 12 months that was maintained thereafter. A drop in SBP of -4.32 mmHg (95% CI -4.84, -3.79) on exposure within the first 3 months was also maintained thereafter. Reductions in BMI and body weight stabilised by 6 months at -0.82 kg/m² (95% CI -0.87, -0.77) and -2.20 kg (95% CI -2.34, -2.06) and were maintained thereafter. eGFR declined initially by -1.81 ml min^-1 [1.73 m]^-2 (95% CI -2.10, -1.52) at 3 months but varied thereafter. There were no significant effects of cumulative drug exposure on safety outcomes.

CONCLUSIONS/INTERPRETATION

Dapagliflozin exposure was associated with reductions in HbA_1c, SBP, body weight and BMI that were at least as large as in clinical trials. Dapagliflozin also prevented the expected rise in HbA_1c and SBP over the period of study.