In the context of survival analysis, calibration refers to the agreement between predicted probabilities and observed event rates or frequencies of the outcome within a given duration of time. We ...aimed to describe and evaluate methods for graphically assessing the calibration of survival models. We focus on hazard regression models and restricted cubic splines in conjunction with a Cox proportional hazards model. We also describe modifications of the Integrated Calibration Index, of E50 and of E90. In this context, this is the average (respectively, median or 90th percentile) absolute difference between predicted survival probabilities and smoothed survival frequencies. We conducted a series of Monte Carlo simulations to evaluate the performance of these calibration measures when the underlying model has been correctly specified and under different types of model mis‐specification. We illustrate the utility of calibration curves and the three calibration metrics by using them to compare the calibration of a Cox proportional hazards regression model with that of a random survival forest for predicting mortality in patients hospitalized with heart failure. Under a correctly specified regression model, differences between the two methods for constructing calibration curves were minimal, although the performance of the method based on restricted cubic splines tended to be slightly better. In contrast, under a mis‐specified model, the smoothed calibration curved constructed using hazard regression tended to be closer to the true calibration curve. The use of calibration curves and of these numeric calibration metrics permits for a comprehensive comparison of the calibration of competing survival models.
The use of evidence from clinical trials to support decisions for individual patients is a form of "reference class forecasting": implicit predictions for an individual are made on the basis of ...outcomes in a reference class of "similar" patients treated with alternative therapies. Evidence based medicine has generally emphasized the broad reference class of patients qualifying for a trial. Yet patients in a trial (and in clinical practice) differ from one another in many ways that can affect the outcome of interest and the potential for benefit. The central goal of personalized medicine, in its various forms, is to narrow the reference class to yield more patient specific effect estimates to support more individualized clinical decision making. This article will review fundamental conceptual problems with the prediction of outcome risk and heterogeneity of treatment effect (HTE), as well as the limitations of conventional (one-variable-at-a-time) subgroup analysis. It will also discuss several regression based approaches to "predictive" heterogeneity of treatment effect analysis, including analyses based on "risk modeling" (such as stratifying trial populations by their risk of the primary outcome or their risk of serious treatment-related harms) and analysis based on "effect modeling" (which incorporates modifiers of relative effect). It will illustrate these approaches with clinical examples and discuss their respective strengths and vulnerabilities.
Objectives The study aimed to (i) determine the influence of poor health on competing exit routes from paid employment among older workers in Europe, (ii) assess whether these risks are different ...among welfare state regimes in Europe, and (iii) evaluate differences in estimates between two different competing risk approaches. Methods The study population consisted of 5273 respondents (6-years follow-up) from the Survey of Health, Ageing, and Retirement in Europe (SHARE). The effect of poor health on exit routes from paid employment was assessed with a cause-specific Cox model and a Fine ＆ Gray (F＆G) model. These two competing risk analyses were used to calculate absolute risks of labor force exit among welfare state regimes in Europe. Results In both models, poor health was a risk factor for disability benefit hazard ratio (HR) 3.36; subdistribution hazard ratio (SHR) 3.22, and unemployment (HR 1.43, SHR 1.32). Both models produced similar absolute risks. In countries with a Bismarckian welfare state regime, low-educated older workers living alone and in poor health had an 11% risk of disability benefit, 7% of unemployment, 46% of early retirement, and 7% of becoming economically inactive. In countries with a Scandinavian welfare state regime, the risks were 10%, 7%, 29%, and 3%, respectively, and in Southern European welfare state regimes 4%, 5%, 35%, and 7%. Conclusions Workers with poor health are more likely to leave the labor force than workers with good health. The absolute risks of early retirement and becoming economically inactive were lowest in countries with a Scandinavian welfare state regime. For disability benefit and unemployment, absolute risks were lowest in Southern European welfare state regimes. The direct estimation of absolute risks of leaving the labor force in the presence of competing exit routes is an appealing feature of the F＆G model.
Summary Background Incisional hernia is a frequent long-term complication after abdominal surgery, with a prevalence greater than 30% in high-risk groups. The aim of the PRIMA trial was to evaluate ...the effectiveness of mesh reinforcement in high-risk patients, to prevent incisional hernia. Methods We did a multicentre, double-blind, randomised controlled trial at 11 hospitals in Austria, Germany, and the Netherlands. We included patients aged 18 years or older who were undergoing elective midline laparotomy and had either an abdominal aortic aneurysm or a body-mass index (BMI) of 27 kg/m2 or higher. We randomly assigned participants using a computer-generated randomisation sequence to one of three treatment groups: primary suture; onlay mesh reinforcement; or sublay mesh reinforcement. The primary endpoint was incidence of incisional hernia during 2 years of follow-up, analysed by intention to treat. Adjusted odds ratios (ORs) were estimated by logistic regression. This trial is registered at ClinicalTrials.gov , number NCT00761475. Findings Between March, 2009, and December, 2012, 498 patients were enrolled to the study, of whom 18 were excluded before randomisation. Therefore, we included 480 patients in the primary analysis: 107 were assigned primary suture only, 188 were allocated onlay mesh reinforcement, and 185 were assigned sublay mesh reinforcement. 92 patients were identified with an incisional hernia, 33 (30%) who were allocated primary suture only, 25 (13%) who were assigned onlay mesh reinforcement, and 34 (18%) who were assigned sublay mesh reinforcement (onlay mesh reinforcement vs primary suture, OR 0·37, 95% CI 0·20–0·69; p=0·0016; sublay mesh reinforcement vs primary suture, 0·55, 0·30–1·00; p=0·05). Seromas were more frequent in patients allocated onlay mesh reinforcement (34 of 188) than in those assigned primary suture (five of 107; p=0·002) or sublay mesh reinforcement (13 of 185; p=0·002). The incidence of wound infection did not differ between treatment groups (14 of 107 primary suture; 25 of 188 onlay mesh reinforcement; and 19 of 185 sublay mesh reinforcement). Interpretation A significant reduction in incidence of incisional hernia was achieved with onlay mesh reinforcement compared with sublay mesh reinforcement and primary suture only. Onlay mesh reinforcement has the potential to become the standard treatment for high-risk patients undergoing midline laparotomy. Funding Baxter; B Braun Surgical SA.
Complex percutaneous coronary intervention (PCI) is associated with higher ischemic risk, which can be mitigated by long-term dual antiplatelet therapy (DAPT). However, concomitant high bleeding risk ...(HBR) may be present, making it unclear whether short- or long-term DAPT should be prioritized.
This study investigated the effects of ischemic (by PCI complexity) and bleeding (by PRECISE-DAPT PREdicting bleeding Complications in patients undergoing stent Implantation and SubsequEnt Dual AntiPlatelet Therapy score) risks on clinical outcomes and on the impact of DAPT duration after coronary stenting.
Complex PCI was defined as ≥3 stents implanted and/or ≥3 lesions treated, bifurcation stenting and/or stent length >60 mm, and/or chronic total occlusion revascularization. Ischemic and bleeding outcomes in high (≥25) or non-high (<25) PRECISE-DAPT strata were evaluated based on randomly allocated duration of DAPT.
Among 14,963 patients from 8 randomized trials, 3,118 underwent complex PCI and experienced a higher rate of ischemic, but not bleeding, events. Long-term DAPT in non-HBR patients reduced ischemic events in both complex (absolute risk difference: −3.86%; 95% confidence interval: −7.71 to +0.06) and noncomplex PCI strata (absolute risk difference: −1.14%; 95% confidence interval: −2.26 to −0.02), but not among HBR patients, regardless of complex PCI features. The bleeding risk according to the Thrombolysis In Myocardial Infarction scale was increased by long-term DAPT only in HBR patients, regardless of PCI complexity.
Patients who underwent complex PCI had a higher risk of ischemic events, but benefitted from long-term DAPT only if HBR features were not present. These data suggested that when concordant, bleeding, more than ischemic risk, should inform decision-making on the duration of DAPT.
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Summary
Studies on the conditional life expectancy of patients with chronic myeloid leukaemia (CML) are lacking. Using data from the Netherlands Cancer Registry, we examined the life expectancy of ...patients with CML in the Netherlands diagnosed during 1989–2018. As of the early 2010s, the life expectancy of patients with CML who survived several years after diagnosis came narrowly close to the general population’s life expectancy, regardless of age. This finding can essentially be ascribed to the introduction and broader application of tyrosine kinase inhibitors (TKIs) and provide optimism to patients with CML who can look forward to a near‐normal life expectancy in a modern TKI era.
Heterogeneity of treatment effect (HTE) refers to the nonrandom variation in the magnitude or direction of a treatment effect across levels of a covariate, as measured on a selected scale, against a ...clinical outcome. In randomized controlled trials (RCTs), HTE is typically examined through a subgroup analysis that contrasts effects in groups of patients defined "1 variable at a time" (for example, male vs. female or old vs. young). The authors of this statement present guidance on an alternative approach to HTE analysis, "predictive HTE analysis." The goal of predictive HTE analysis is to provide patient-centered estimates of outcome risks with versus without the intervention, taking into account all relevant patient attributes simultaneously. The PATH (Predictive Approaches to Treatment effect Heterogeneity) Statement was developed using a multidisciplinary technical expert panel, targeted literature reviews, simulations to characterize potential problems with predictive approaches, and a deliberative process engaging the expert panel. The authors distinguish 2 categories of predictive HTE approaches: a "risk-modeling" approach, wherein a multivariable model predicts the risk for an outcome and is applied to disaggregate patients within RCTs to define risk-based variation in benefit, and an "effect-modeling" approach, wherein a model is developed on RCT data by incorporating a term for treatment assignment and interactions between treatment and baseline covariates. Both approaches can be used to predict differential absolute treatment effects, the most relevant scale for clinical decision making. The authors developed 4 sets of guidance: criteria to determine when risk-modeling approaches are likely to identify clinically important HTE, methodological aspects of risk-modeling methods, considerations for translation to clinical practice, and considerations and caveats in the use of effect-modeling approaches. The PATH Statement, together with its explanation and elaboration document, may guide future analyses and reporting of RCTs.
We aimed to compare the performance of different regression modeling approaches for the prediction of heterogeneous treatment effects.
We simulated trial samples (n = 3,600; 80% power for a treatment ...odds ratio of 0.8) from a superpopulation (N = 1,000,000) with 12 binary risk predictors, both without and with six true treatment interactions. We assessed predictions of treatment benefit for four regression models: a “risk model” (with a constant effect of treatment assignment) and three “effect models” (including interactions of risk predictors with treatment assignment). Three novel performance measures were evaluated: calibration for benefit (i.e., observed vs. predicted risk difference in treated vs. untreated), discrimination for benefit, and prediction error for benefit.
The risk modeling approach was well-calibrated for benefit, whereas effect models were consistently overfit, even with doubled sample sizes. Penalized regression reduced miscalibration of the effect models considerably. In terms of discrimination and prediction error, the risk modeling approach was superior in the absence of true treatment effect interactions, whereas penalized regression was optimal in the presence of true treatment interactions.
A risk modeling approach yields models consistently well calibrated for benefit. Effect modeling may improve discrimination for benefit in the presence of true interactions but is prone to overfitting. Hence, effect models—including only plausible interactions—should be fitted using penalized regression.
Background Liver surgery for perihilar cholangiocarcinoma (PHC) is associated with postoperative mortality ranging from 5% to 18%. The aim of this study was to develop a preoperative risk score for ...postoperative mortality after liver resection for PHC, and to assess the effect of biliary drainage of the future liver remnant (FLR). Study Design A consecutive series of 287 patients submitted to major liver resection for presumed PHC between 1997 and 2014 at 2 Western centers was analyzed; 228 patients (79%) underwent preoperative drainage for jaundice. Future liver remnant volumes were calculated with CT volumetry and completeness of FLR drainage was assessed on imaging. Logistic regression was used to develop a mortality risk score. Results Postoperative mortality at 90 days was 14% and was independently predicted by age (odds ratio OR per 10 years = 2.1), preoperative cholangitis (OR = 4.1), FLR volume <30% (OR = 2.9), portal vein reconstruction (OR = 2.3), and incomplete FLR drainage in patients with FLR volume <50% (OR = 2.8). The risk score showed good discrimination (area under the curve = 0.75 after bootstrap validation) and ranking patients in tertiles identified 3 (ie low, intermediate, and high) risk subgroups with predicted mortalities of 2%, 11%, and 37%. No postoperative mortality was observed in 33 undrained patients with FLR volumes >50%, including 10 jaundiced patients (median bilirubin level 11 mg/dL). Conclusions The mortality risk score for patients with resectable PHC can be used for patient counseling and identification of modifiable risk factors, which include FLR volume, FLR drainage status, and preoperative cholangitis. We found no evidence to support preoperative biliary drainage in patients with an FLR volume >50%.
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