Quantifying absolute treatment effect heterogeneity for time-to-event outcomes across different risk strata: divergence of conclusions with risk difference and restricted mean survival difference.

Background: Risk-based analyses are increasingly popular for understanding heterogeneous treatment effects (HTE) in clinical trials. For time-to-event analyses, the assumption that high-risk patients benefit most on the clinically important absolute scale when hazard ratios (HRs) are constant across risk strata might not hold. Absolute treatment effects can be measured as either the risk difference (RD) at a given time point or the difference in restricted mean survival time (ΔRMST) which aligns more closely with utilitarian medical decision-making frameworks.

Derivation and Validation of the PRECISE-HBR Score to Predict Bleeding After Percutaneous Coronary Intervention.

Background: Accurate bleeding risk stratification after percutaneous coronary intervention (PCI) is important for treatment individualization. However, there is still an unmet need for a more precise and standardized identification of high bleeding risk patients. We derived and validated a novel bleeding risk score by augmenting the PRECISE-DAPT score with the Academic Research Consortium for High Bleeding Risk (ARC-HBR) criteria.

Ten-year survival benefit and appropriateness of surgical versus percutaneous revascularization in synergy between percutaneous coronary intervention with Taxus and cardiac surgery randomized trial.

Objectives: Average treatment effects from randomized trials do not reflect the heterogeneity of an individual's response to treatment. This study evaluates the appropriate proportions of patients for coronary artery bypass grafting, or percutaneous intervention based on the predicted/observed ratio of 10-year all-cause mortality in the SYNTAX population.

Methods: The study included 1800 randomized patients and 1275 patients in the nested percutaneous (n = 198) or surgical (n = 1077) registries.

Guidance for unbiased predictive information for healthcare decision-making and equity (GUIDE): considerations when race may be a prognostic factor.

Clinical prediction models (CPMs) are tools that compute the risk of an outcome given a set of patient characteristics and are routinely used to inform patients, guide treatment decision-making, and resource allocation. Although much hope has been placed on CPMs to mitigate human biases, CPMs may potentially contribute to racial disparities in decision-making and resource allocation. While some policymakers, professional organizations, and scholars have called for eliminating race as a variable from CPMs, others raise concerns that excluding race may exacerbate healthcare disparities and this controversy remains unresolved.

Comparative effectiveness of 6x R-CHOP21 versus 6x R-CHOP21 + 2 R for patients with advanced-stage diffuse large B-cell lymphoma.

First-line treatment for advanced-stage diffuse large B-cell lymphoma (DLBCL) typically involves 6x R-CHOP21 or 6x R-CHOP21 with two additional rituximab administrations (6x R-CHOP21 + 2 R). In contemporary practice, this treatment choice might be guided by interim PET scan results. This nationwide, population-based study investigates the comparative effectiveness of these treatment regimens in an era where interim PET-guided treatment decisions were not standard practice.

Experienced financial toxicity among long-term cancer survivors: results from a national cross-sectional survey.

Purpose: Financial toxicity, the subjective distress caused by objective financial burden, significantly impacts cancer survivors. Yet, enduring effects on survivors remain unclear. Therefore, we investigated the experienced objective financial burden and subjective financial distress in long-term cancer survivors.

Pitfalls of single-study external validation illustrated with a model predicting functional outcome after aneurysmal subarachnoid hemorrhage.

Background: Prediction models are often externally validated with data from a single study or cohort. However, the interpretation of performance estimates obtained with single-study external validation is not as straightforward as assumed. We aimed to illustrate this by conducting a large number of external validations of a prediction model for functional outcome in subarachnoid hemorrhage (SAH) patients.

Weighted metrics are required when evaluating the performance of prediction models in nested case-control studies.

Background: Nested case-control (NCC) designs are efficient for developing and validating prediction models that use expensive or difficult-to-obtain predictors, especially when the outcome is rare. Previous research has focused on how to develop prediction models in this sampling design, but little attention has been given to model validation in this context. We therefore aimed to systematically characterize the key elements for the correct evaluation of the performance of prediction models in NCC data.

Patent Foramen Ovale Closure in Older Patients With Stroke: Patient Selection for Trial Feasibility.

Background And Objectives: Whether patent foramen ovale (PFO) closure benefits older patients with PFO and cryptogenic stroke is unknown because randomized controlled trials (RCTs) have predominantly enrolled patients younger than 60 years of age. Our objective was to estimate anticipated effects of PFO closure in older patients to predict the numbers needed to plan an RCT.

Methods: Effectiveness estimates are derived from major observational studies (Risk of Paradoxical Embolism [RoPE] Study and Oxford Vascular Study, together referred to as the "RoPE-Ox" database) and all 6 major RCTs (Systematic, Collaborative, PFO Closure Evaluation [SCOPE] Consortium).

Development and validation of a novel model to predict recurrence-free survival and melanoma-specific survival after sentinel lymph node biopsy in patients with melanoma: an international, retrospective, multicentre analysis.

Background: The introduction of adjuvant systemic treatment for patients with high-risk melanomas necessitates accurate staging of disease. However, inconsistencies in outcomes exist between disease stages as defined by the American Joint Committee on Cancer (8th edition). We aimed to develop a tool to predict patient-specific outcomes in people with melanoma rather than grouping patients according to disease stage.

Personalized decision-making for aneurysm treatment of aneurysmal subarachnoid hemorrhage: development and validation of a clinical prediction tool.

Background: In patients with aneurysmal subarachnoid hemorrhage suitable for endovascular coiling and neurosurgical clip-reconstruction, the aneurysm treatment decision-making process could be improved by considering heterogeneity of treatment effect and durability of treatment. We aimed to develop and validate a tool to predict individualized treatment benefit of endovascular coiling compared to neurosurgical clip-reconstruction.

Methods: We used randomized data (International Subarachnoid Aneurysm Trial, n = 2143) to develop models to predict 2-month functional outcome and to predict time-to-rebleed-or-retreatment.

Prevention of incisional hernia with prophylactic onlay and sublay mesh reinforcement vs. primary suture only in midline laparotomies (PRIMA): long-term outcomes of a multicentre, double-blind, randomised controlled trial.

Background: Incisional hernia occurs approximately in 40% of high-risk patients after midline laparotomy. Prophylactic mesh placement has shown promising results, but long-term outcomes are needed. The present study aimed to assess the long-term incisional hernia rates of the previously conducted PRIMA trial with radiological follow-up.

Can Machine Learning Aid the Selection of Percutaneous vs Surgical Revascularization?

Background: In patients with 3-vessel coronary artery disease (CAD) and/or left main CAD, individual risk prediction plays a key role in deciding between percutaneous coronary intervention (PCI) and coronary artery bypass grafting (CABG).

Objectives: The aim of this study was to assess whether these individualized revascularization decisions can be improved by applying machine learning (ML) algorithms and integrating clinical, biological, and anatomical factors.

Methods: In the SYNTAX (Synergy between PCI with Taxus and Cardiac Surgery) study, ML algorithms (Lasso regression, gradient boosting) were used to develop a prognostic index for 5-year death, which was combined, in the second stage, with assigned treatment (PCI or CABG) and prespecified effect-modifiers: disease type (3-vessel or left main CAD) and anatomical SYNTAX score.

Integrated care in patients with atrial fibrillation- a predictive heterogeneous treatment effect analysis of the ALL-IN trial.

Introduction: Integrated care is effective in reducing all-cause mortality in patients with atrial fibrillation (AF) in primary care, though time and resource intensive. The aim of the current study was to assess whether integrated care should be directed at all AF patients equally.

Methods: The ALL-IN trial (n = 1,240 patients, median age 77 years) was a cluster-randomized trial in which primary care practices were randomized to provide integrated care or usual care to AF patients aged 65 years and older.

Personalised decision making to predict absolute metastatic risk in cutaneous squamous cell carcinoma: development and validation of a clinico-pathological model.

Background: Cutaneous squamous cell carcinoma (cSCC) is a common skin cancer, affecting more than 2 million people worldwide yearly and metastasising in 2-5% of patients. However, current clinical staging systems do not provide estimates of absolute metastatic risk, hence missing the opportunity for more personalised treatment advice. We aimed to develop a clinico-pathological model that predicts the probability of metastasis in patients with cSCC.

Number of life-years lost at the time of diagnosis and several years post-diagnosis in patients with solid malignancies: a population-based study in the Netherlands, 1989-2019.

Background: Loss of life expectancy (LOLE) may provide more intuitive information on the impact of cancer than relative survival over a fixed time horizon (e.g., 5-year relative survival).

External validation of 18 F-FDG PET-based radiomic models on identification of residual oesophageal cancer after neoadjuvant chemoradiotherapy.

Objectives: Detection of residual oesophageal cancer after neoadjuvant chemoradiotherapy (nCRT) is important to guide treatment decisions regarding standard oesophagectomy or active surveillance. The aim was to validate previously developed 18 F-FDG PET-based radiomic models to detect residual local tumour and to repeat model development (i.e.

Prognostic Models for Global Functional Outcome and Post-Concussion Symptoms Following Mild Traumatic Brain Injury: A Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) Study.

After mild traumatic brain injury (mTBI), a substantial proportion of individuals do not fully recover on the Glasgow Outcome Scale Extended (GOSE) or experience persistent post-concussion symptoms (PPCS). We aimed to develop prognostic models for the GOSE and PPCS at 6 months after mTBI and to assess the prognostic value of different categories of predictors (clinical variables; questionnaires; computed tomography [CT]; blood biomarkers). From the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study, we included participants aged 16 or older with Glasgow Coma Score (GCS) 13-15.

Estimating individualized treatment effects from randomized controlled trials: a simulation study to compare risk-based approaches.

Background: Baseline outcome risk can be an important determinant of absolute treatment benefit and has been used in guidelines for "personalizing" medical decisions. We compared easily applicable risk-based methods for optimal prediction of individualized treatment effects.

Methods: We simulated RCT data using diverse assumptions for the average treatment effect, a baseline prognostic index of risk, the shape of its interaction with treatment (none, linear, quadratic or non-monotonic), and the magnitude of treatment-related harms (none or constant independent of the prognostic index).