Therneau, Terry M.

Background/aims The goal of this article is to illustrate the utility of multi-state models in cancer clinical trials. Our specific aims are to describe multi-state models and how they differ from standard survival methods, to illustrate how multi-state models can facilitate deeper understanding of the treatment effect on multiple paths along the disease process that patients could experience in cancer clinical trials, to explain the differences between multi-state models and time-dependent Cox models, and to briefly describe available software to conduct such analyses. Methods Data from 717 newly diagnosed acute myeloid leukemia patients who enrolled in the CALGB 10603 trial were used as an illustrative example. The current probability-in-state was estimated using the Aalen–Johansen estimator. The restricted mean time in state was calculated as the area under the probability-in-state curves. Cox-type regression was used to evaluate the effect of midostaurin on the various clinical paths. Simulation was conducted using a newly constructed shiny application. All analyses were performed using the R software. Results Multi-state model analyses of CALGB 10603 suggested that the overall improvement in survival with midostaurin seen in the primary analysis possibly resulted from a higher complete remission rate in combination with a lower risk of relapse and of death after complete remission in patients treated with midostaurin. Simulation results, in a three-state illness-death without recovery model, demonstrate that multi-state models and time-dependent Cox models evaluate treatment effects from different frameworks. Conclusion Multi-state models allow detailed evaluation of treatment effects in complex clinical trial settings where patients can experience multiple paths between study enrollment and the final outcome. Multi-state models can be used as a complementary tool to standard survival analyses to provide deeper insights to the effects of treatment in trial settings with complex disease process.

Background: Etiologic differences in mild cognitive impairment (MCI) subtypes may impact mortality. Objective: To assess the rate of death in MCI overall, and by subtype, in the population-based Mayo Clinic Study of Aging. Methods: Participants aged 70–89 years at enrollment were clinically evaluated at baseline and 15-month intervals to assess diagnoses of MCI and dementia. Mortality in MCI cases versus cognitively normal (CN) individuals was estimated using Cox proportional hazards models. Results: Over a median follow-up of 5.8 years, 331 of 862 (38.4%) MCI cases and 224 of 1,292 (17.3%) cognitively normal participants died. Compared to CN individuals, mortality was elevated in persons with MCI (hazard ratio [HR] = 2.03; 95% CI: 1.61 to 2.55), and was higher for non-amnestic MCI (naMCI; HR = 2.47; 95% CI: 1.80 to 3.39) than for amnestic MCI (aMCI; HR = 1.89; 95% CI: 1.48 to 2.41) after adjusting for confounders. Mortality varied significantly by sex, education, history of heart disease, and engaging in moderate physical exercise (p for interaction <0.05 for all). Mortality rate estimates were highest in MCI cases who were men, did not exercise, had heart disease, and had higher education versus CN without these factors, and for naMCI cases versus aMCI cases without these factors. Conclusions: These findings suggest stronger impact of etiologic factors on naMCI mortality. Prevention of heart disease, exercise vigilance, may reduce MCI mortality and delayed MCI diagnosis in persons with higher education impacts mortality.

Background Sex-based disparities in liver transplantation (LT) are incompletely understood. We assessed the role of height, Model for End-Stage Liver Disease (MELD), MELD-Na, and exception points in the disparate access to LT. Methods Adults waitlisted for LT at Organ Procurement and Transplantation Network between 2002 and 2013 were included. Covariates associated with likelihood of LT were analyzed by Cox proportional model. In a separate cohort of waitlisted adults with glomerular filtration rate measurement by iothalamate clearance (n = 611), we determined the number of creatinine-derived MELD points in men versus women, across all ranges of glomerular filtration rate. The impact of correcting the MELD score deficit in women on LT was modeled. Results Among 90 720 Organ Procurement and Transplantation Network registrants, women had higher mortality than men (4 years after listing: 22% vs 18%, P < 0.0001), and lower likelihood of LT (49% vs 58%, P < 0.0001); women were 20% less likely to be transplanted (hazard ratio, 0.80; 95% confidence interval, 0.78-0.81). Differences in height and MELD exception scores accounted for most of the LT deficit in women (hazard ratio, 0.91; 95% confidence interval, 0.89-0.94). Women received between 1 and 2.4 fewer creatinine-derived MELD points than men with similar renal dysfunction. MELD-Na worsened the gender disparity. Addition of 1 or 2 MELD points to women significantly impacted LT access. Conclusions Differences in height and MELD exception points explained most of the sex-based disparity in LT. Additionally, MELD score underestimated disease severity in women by up to 2.4 points and MELD Na exacerbated this disparity. The degree of underestimation based on MELD had significant impact on allocation.