exp neoplasms/ OR cancer*.mp. OR neoplasm*.mp. OR 3,363,037 Publication type: observational studies (cohorts and case-controls)

Transcription

1 Supplementary Table S1. Search strategy for observational studies on long-acting insulin analogues and cancer using Medline and Embase databases from January 2000 to October 8, 2014 Medline Description Key terms Records Patients with type 1 or type 2 diabetes exp Diabetes Mellitus, Type 1/ OR exp Diabetes Mellitus, Type 2/ OR diabet*.mp. 490,207 Insulin glargine or detemir exp Insulins/ OR insulin*.mp. OR glargine.mp. OR Lantus.mp. OR detemir.mp. OR Levemir.mp. 336,783 Cancer exp Neoplasms/ OR cancer*.mp. OR neoplasm*.mp. OR tumor*.mp. OR tumour*.mp. OR malignan*.mp. 3,363,037 Publication type: observational studies (cohorts and case-controls) exp cohort studies/ OR exp case control studies/ OR observational study/ OR observational study as topic/ OR Epidemiologic studies/ OR Registries/ OR (cohort adj (study or studies)).tw. OR cohort*.tw. OR (case adj (control or cohort) adj (study or studies)).tw. OR (nested 1,801,696 case control adj (study or studies)).tw. OR (case adj (control or controls or cohort or cohorts)).tw. OR (observational adj (study or studies)).tw. OR (epidemiologic$ adj (study or studies)).tw. PICO and publication type 1,576 Limits Publication year: 2000-current 1,379 Language: English 1,303 Embase Description Key terms Records Patients with type 1 or type 2 exp insulin dependent diabetes mellitus/ OR exp non diabetes insulin dependent diabetes mellitus/ OR diabet*.mp. 762,737 Insulin glargine or detemir exp insulin derivative/ OR insulin*.mp. OR glargine.mp. OR Lantus.mp. OR detemir.mp. OR Levemir.mp. 574,961 Cancer exp neoplasms/ OR cancer*.mp. OR neoplasm*.mp. OR tumor*.mp. OR tumour*.mp. OR malignan*.mp. 4,412,637 Publication type: observational studies (cohorts and casecontrols) observational study/ OR cohort analysis/ OR retrospective study/ OR prospective study/ OR longitudinal study/ OR case control study/ OR register/ OR (cohort adj (study or studies)).tw. OR cohort*.tw. OR (case adj (control or cohort) adj (study or studies)).tw. OR (nested case control 1,302,843 adj (study or studies)).tw. OR (case adj (control or controls or cohort or cohorts)).tw. OR (observational adj (study or studies)).tw. OR (epidemiologic$ adj (study or studies)).tw. PICO and publication type 3,380 Limits Publication year: 2000-current 3,254 Language: English 3,114

2 Supplementary Table S2. Solutions to methodological issues present in literature examining longacting insulin analogues and cancer Type of bias or methodological issues Immortal time bias Time-lag bias Time-window bias Residual confounding Disease latency, protopathic bias, and detection bias Prevalent users Design For exposure-based cohorts (e.g., enter the cohort based on nth prescription(s) of insulin), define cohort entry or time zero (t 0 ) as the nth prescription exposure and comparator. Alternatively, a nested-case control study can be used because of its inherent time-dependent characteristic. Match on duration of disease for the exposed and comparator groups. Match cases and controls on duration of disease. Use an active comparator with similar indications which will help reduce confounding. Cohorts: Lagging the exposure by n amount of years from cohort entry Case-controls: Lag the exposure by n amount of years prior to case or control index date. Restrict the cohort to a minimum period of non-use (wash-out) prior to t 0. Solutions Analysis Use a time-dependent analysis (e.g., Cox model with a time-dependent exposure) to classify unexposed person-time until meeting the exposure definition. References (1; 2) (3) (3; 4) (5) (3; 6) (7)

3 Supplementary Figure 1. Flow chart of included and excluded studies on insulin glargine and risk of cancer identified from the literature search from January 2000 to October 8, 2014

4 Supplementary Figure 2. Forest plots of effect estimates from studies on insulin detemir and any cancer incidence from 4 studies

5 Supplementary Figure 3. Graphical representations of immortal time bias. Immortal time refers to a time period in the follow-up where the outcome of interest cannot occur as a result of the study design and analysis (1; 2). This immortal time occurs due to an arbitrary delay period that is imposed (e.g., using at least 12 prescriptions for the medication to define exposure status but with follow-up time beginning with the first prescription). This time period is considered immortal because the patient has to survive (i.e., be free of the outcome of interest) before satisfying the exposure definition. If the patient has the outcome before satisfying the exposure definition, then he or she will be classified as unexposed. This bias occurs when the immortal time period or person-time is misclassified as exposed or excluded from the analysis (2). Immortal time bias may have been introduced based on the definitions of exposure and cohort entry that were used in one cohort study (8). For the predominant user definition, the patient needed to have at least 12 prescriptions of insulin and be exposed 80% of the follow-up time to be considered exposed but the time before the twelfth prescription and meeting the 80% exposure time should be considered unexposed. As a result, the adjusted hazard ratios for any cancers were approximately 0.60, although the results were not statistically significant. The circles ( ) indicate a prescription for insulin glargine and triangles ( ) indicate a prescription for other insulins.

6 Supplementary Figure 4. A illustration of time-lag bias when comparing insulin glargine to other insulins (e.g., human or short-acting insulin), which may be used earlier stages of diabetes and thus introducing confounding by disease duration (3). The arrow represents when the comparison begins.

7 Supplementary Figure 5. Depiction of potential time-window bias, that can occur when cases and controls are not matched on duration of diabetes resulting in differential exposure opportunity (3; 4). Time-window bias was observed in the population-based case-control study (9). Despite matching on calendar time, time-window bias was potentially present because cases and controls were not matched on duration of diabetes. Consequently, the opportunity for exposure differed between the cases and controls due to the varying diabetes durations (a mean of 14.5 years among cases and 13.2 among controls). While one would expect an increased risk due to the presence of time-window bias, a null effect was observed. This suggests that other biases, such as selection bias resulting from selection of cases and controls from different study bases, may also be present.

8 References 1. Suissa S: Immortal time bias in pharmaco-epidemiology. American journal of epidemiology 2008;167: Levesque LE, Hanley JA, Kezouh A, Suissa S: Problem of immortal time bias in cohort studies: example using statins for preventing progression of diabetes. Bmj 2010;340:b Suissa S, Azoulay L: Metformin and the risk of cancer: time-related biases in observational studies. Diabetes care 2012;35: Suissa S, Dell'aniello S, Vahey S, Renoux C: Time-window bias in case-control studies: statins and lung cancer. Epidemiology 2011;22: Schneeweiss S, Patrick AR, Sturmer T, Brookhart MA, Avorn J, Maclure M, Rothman KJ, Glynn RJ: Increasing levels of restriction in pharmacoepidemiologic database studies of elderly and comparison with randomized trial results. Medical care 2007;45:S Tamim H, Monfared AA, LeLorier J: Application of lag-time into exposure definitions to control for protopathic bias. Pharmacoepidemiology and drug safety 2007;16: Ray WA: Evaluating medication effects outside of clinical trials: new-user designs. American journal of epidemiology 2003;158: Blin P, Lassalle R, Dureau-Pournin C, Ambrosino B, Bernard MA, Abouelfath A, Gin H, Le Jeunne C, Pariente A, Droz C, Moore N: Insulin glargine and risk of cancer: a cohort study in the French National Healthcare Insurance Database. Diabetologia 2012;55: Grimaldi-Bensouda L, Cameron D, Marty M, Barnett AH, Penault-Llorca F, Pollak M, Charbonnel B, Riddle M, Mignot L, Boivin J-F: Risk of breast cancer by individual insulin use: an international multicenter study. Diabetes care 2014;37: