Michal Abrahamowicz’s research while affiliated with McGill University Health Centre and other places

Excess body fatness in late adulthood has been observed to increase ovarian cancer risk, but the association is relatively weak. Body fatness can change over time, and timing may differently influence risk. We used a life course epidemiology approach to identify whether the relation between body fatness and ovarian cancer risk is best described by a critical period, accumulation or sensitive period hypothesis. In a population-based case-control study of ovarian cancer in Montreal, Canada (2011-16), data on body mass index (BMI) at each decade starting at age 20 was available. Among 363 cases and 707 controls aged ≥ 50 years, we used a Bayesian relevant life course exposure model to estimate the relative importance of BMI for three pre-specified periods across the adult life course, i.e., early childbearing years, late childbearing years, and peri/postmenopause, on ovarian cancer risk. The accumulation hypothesis best described BMI in relation to ovarian cancer overall, with an odds ratio (OR) for the lifetime effect of BMI (per 5 kg/m² increase) of 1.10 (95% credible interval [CrI]: 0.90–1.35). For invasive ovarian cancer, the OR (95% CrI) for the lifetime effect was 1.16 (0.92–1.48), with BMI during early childbearing years showing the highest relative importance, suggesting this may be a sensitive period. For borderline cancer, the lifetime effect OR was not strongly supportive of an association (OR: 0.90, 95% CrI: 0.53–1.32). The results suggest that a sensitive period of early childbearing years is a candidate hypothesis for further investigation.

Aim: We sought to model the cumulative, long-term effect of self- reported opioid use using weighted cumulative exposure (WCE) models on change in Veterans Aging Cohort (VACS) Index score, a measure of HIV disease severity, among people with HIV (PWH). Methods: ART-exposed PWH who enrolled from December 2005 to November 2017 in the AIDS Care Cohort to Evaluate Exposure to Survival Services prospective cohort study in Vancouver, Canada were studied. Baseline surveys collected sociodemographic and substance use information, and follow-up occurred every six months. Opioid use was defined as self-reported illicit use of prescription opioids and/or heroin in the past six months. The outcome was VACS Index score. WCE models estimated the relative impact of past opioid use on the current change in VACS Index score. Conventional linear mixed models were used as a comparative reference to the WCE models. Results: The study comprised 483 ART-exposed PWH, 21.2% (n=102) of whom used opioids at baseline. Median age was 44.1 years, 42.4% identified as Indigenous, and 34.2% were female. Median VACS Index score at baseline was 21 (IQR= 12 – 29), and median follow-up time was 6.7 years (IQR= 3.5 – 8.6 years). The results from the WCE model indicated that opioid use from approxi- mately the past 1.5 – 3 years were associated with statistically significant decreases in the current VACS index score. The conven- tional linear mixed model estimated that ever using opioids in the past 6 months resulted in an average 0.04 point (95%CI: -0.83 – 0.76) decrease in VACS Index score. Conclusions: WCE models capture dynamic patterns of self- reported opioid use that may inform more realistic modeling of substance use behavior on health outcomes.

The evidence from previous studies of serum 25-hydroxyvitamin D (25(OH)D) and ovarian cancer risk is not conclusive. However, the 25(OH)D levels were generally only measured in late adulthood, which may not capture the etiologically relevant exposure periods. We investigated predicted 25(OH)D over the adult lifetime in relation to ovarian cancer risk in a population-based case-control study conducted from 2011 to 2016 in Montreal, Canada (n = 490 cases and 896 controls). Predicted 25(OH)D was computed using previously validated regression models. Unconditional multivariable logistic regression models were used to estimate adjusted odds ratios (aORs) and 95% CIs for average predicted 25(OH)D over the adult lifetime and ovarian cancer risk. In addition, the relative importance of different periods of past 25(OH)D exposure was explored using a weighted cumulative exposure (WCE) model. For each 20-nmol/L increase in average predicted 25(OH)D over the adult lifetime, the aOR (95% CI) was 0.73 (0.55-0.96). In WCE analyses, the inverse association was strongest for exposures 5 to 20 years and 35 to 55 years prior to diagnosis, with aORs (95% CIs) of 0.82 (0.69-0.94) and 0.79 (0.66-1.02), respectively, for each 20-nmol/L increase in predicted 25(OH)D. These results support an inverse association between 25(OH)D levels in adulthood and ovarian cancer risk. This article is part of a Special Collection on Gynecological Cancers.

Quantitative bias analysis (QBA) permits assessment of the expected impact of various imperfections of the available data on the results and conclusions of a particular real-world study. This article extends QBA methodology to multivariable time-to-event analyses with right-censored endpoints, possibly including time-varying exposures or covariates. The proposed approach employs data-driven simulations, which preserve important features of the data at hand while offering flexibility in controlling the parameters and assumptions that may affect the results. First, the steps required to perform data-driven simulations are described, and then two examples of real-world time-to-event analyses illustrate their implementation and the insights they may offer. The first example focuses on the omission of an important time-invariant predictor of the outcome in a prognostic study of cancer mortality, and permits separating the expected impact of confounding bias from non-collapsibility. The second example assesses how imprecise timing of an interval-censored event – ascertained only at sparse times of clinic visits – affects its estimated association with a time-varying drug exposure. The simulation results also provide a basis for comparing the performance of two alternative strategies for imputing the unknown event times in this setting. The R scripts that permit the reproduction of our examples are provided.

Background In recent years, age at liver transplantation (LT) has markedly increased. In the context of organ shortage, we investigated the impact of recipient age on post‐transplantation mortality. Methods All adult patients who received a first LT between 2007 and 2017 were included in this cross‐sectional study. Recipients' characteristics at the time of listing, donor and surgery data, post‐operative complications and follow‐up of vital status were retrieved from the national transplantation database. The impact of age on 5‐year overall mortality post‐LT was estimated using a flexible multivariable parametric model which was also used to estimate the association between age and 10‐year net survival, accounting for expected age‐ and sex‐related mortality. Results Among the 7610 patients, 21.4% were aged 60–65 years, and 15.7% over 65. With increasing age, comorbidities increased but severity of liver disease decreased. Older recipient age was associated with decreased observed survival at 5 years after LT ( p < .001), with a significant effect particularly during the first 2 years. The linear increase in the risk of death associated with age does not allow any definition of an age's threshold for LT ( p = .832). Other covariates associated with an increased risk of 5‐year death were dialysis and mechanical ventilation at transplant, transfusion during LT, hepatocellular carcinoma and donor age. Ten‐year flexible net survival analysis confirmed these results. Conclusion Although there was a selection process for older recipients, increasing age at LT was associated with an increased risk of death, particularly in the first years after LT.

We assessed whether contemporary immunosuppression agents were associated with cancer among kidney transplant recipients (KTR), and if this association varied by age and sex. We studied a retrospective province‐wide cohort of primary KTR (1997–2016). Employing multivariable Cox models, we estimated associations of cumulative doses of prednisone, mycophenolate and tacrolimus administered over the past 10 years, lagged by 2 years, with the incidence of primary malignant neoplasms (PMN). We assessed interactions with age and sex. To assess the impact of exposure recency, we used weighted cumulative exposure (WCE) modeling. Among 1064 KTR, 108 (10.2%) developed PMN over median follow‐up of 73 months (interquartile range: 32–120). Adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) of 0.96 (0.64–1.43), 1.34 (0.96–1.86), and 1.06 (0.88–1.29) were estimated for cumulative daily doses of prednisone (5 mg), mycophenolate (1000 mg), and tacrolimus (2 mg) administered continuously over the past 10 years, respectively. PMN risk associated with cumulative tacrolimus exposure was modified by age (interaction p = .035) and was more pronounced in 15‐year and 30‐year‐old KTR (aHRs of 1.57 [1.08–2.28] and 1.31 [1.03–1.66], respectively) in comparison to older KTR. PMN risk increase associated with higher cumulative mycophenolate dose was more pronounced in females (aHR = 1.86 [1.15–3.00]) than in males (aHR = 1.16 [0.74–1.81]; interaction p = .131). WCE analyses suggested increased PMN risk the higher the mycophenolate doses taken 5–10 years ago. A trend toward increased PMN risk with long‐term mycophenolate exposure, particularly in females, and more pronounced risk with long‐term tacrolimus exposure in younger KTR, identify opportunities for tailored immunosuppression to mitigate cancer risk.