DOI: 10.25934/pr00009841
title: Estimating heterogeneous treatment effects of immunotherapy combination regimens for treatment of advanced/metastatic clear cell renal cell carcinoma: an individual patient data meta-analysis

description: Approximately 430,000 people worldwide are diagnosed with renal cancer annually, of which 18% face advanced/metastatic (where the cancer has spread to other parts of the body) stages at diagnosis, and many progress to such stages later. For advanced clear cell renal cell carcinoma (accRCC) treatment, an aggressive cancer of the kidneys characterised by clear cells that look like soap bubbles, European guidelines (guidance for clinicians on diagnosis and treatment) recommended tyrosine-kinase inhibitors (TKI) - drugs that block enzymes called tyrosine kinases, proteins that play a role in growth and division of cells, in cancer. However, since 2018, four immunotherapy combinations (ipilimumab + nivolumab, lenvatinib + pembrolizumab, axitinib + pembrolizumab, and cabozantinib + nivolumab), which work by boosting the immune system and help the body find and destroy cancer cells, have replaced the previous single treatment therapies (monotherapies) as first-line treatments, showing improved overall survival in clinical trials.

Each of the clinical trials for these combination therapies reveal a nuanced picture. Examining overall survival outcomes, suggests that the benefits of these combination therapies over TKI treatment vary among patient subgroups. Observed heterogeneity (differences) of treatment effects (HTE) across different patient subgroups, raises questions about the applicability of these combinations universally. However, challenges exist in drawing robust conclusions and implementing these findings in clinical practice due to various issues in the data presented so far.

HTE is often explored in trial reports through so-called ‘one-variable-at-a-time’ subgroup analyses, which is the process of exploring one variable (patient characteristic) at a time. This method faces limitations in statistical power due to the small sample sizes, increasing the risk of false findings.  These types of methods may be useful as exploratory or descriptive analyses, and may produce population-level insights, but multiple variables must be jointly considered to generate clinically relevant assessment of HTE. Hence, joint consideration of multiple variables is preferred both from a statistical standpoint as well as from a clinical standpoint. 
The trials requested also employed methods that overlooked essential prognostic factors (things that can indicate the likely outcomes for the patient) like metastatic locations (where the cancer has spread to), patient age and programmed death-ligand 1 (PD-L1) levels. If cancer cells have high amounts of PD-L1 protein, these can turn off the immune system so it can’t attack the cancer cells.

Addressing analytical challenges and reconsidering prognostic classifications are crucial steps in ensuring the clinical relevance and applicability of these findings in renal cancer treatment.
This project will assess the overall survival benefit of immunotherapy combination regimens over single-agent TKI across prognosis-based subgroups of patients (subgroups of patients in the studies, grouped by how long they were expected to live based on their baseline characteristics such as age and clinical risk factors, and regardless of the treatment they received in the study) with previously untreated accRCC, and assess the same across effect-based subgroups (subgroups of patients in the studies, grouped by how well they were expected to respond to the experimental treatment, based on their baseline characteristics such as age and clinical risk factors), by using the pooled individual patient data from the four aforementioned trials.