ReviewCancer2025
Analyses of adverse events and patient-reported outcomes with the toxicity index in cancer clinical trials.
Review in Cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
Abstract
backgroundAdvancements in cancer therapies and improvements in survival have led to an increasing need to understand the impact of treatment on both severe and low-grade persisting symptoms and treatment-related toxicities. The National Cancer Institute launched the Cancer Moonshot Tolerability Consortium in 2018 to develop methods to analyze clinical and patient-reported tolerability data.
methodsThrough this initiative, the toxicity index (TI) was applied in the analysis of clinical trial tolerability data, and its performance was compared to other existing scoring methods. The TI is a tool developed to quantify the cumulative burden of all levels of clinician-graded toxicity data using Common Terminology Criteria for Adverse Events and patient-reported toxicity. This review describes the statistical properties of the TI and highlights key findings on the utility of the TI in summarizing tolerability data and its applications to existing clinical trial data.
resultsCompared to other commonly used summary measures, the TI was shown to be more efficient and increased the statistical power to detect treatment differences. The TI was also applied to existing toxicity and patient-reported symptom data from selected trials, where it was used to predict dose-limiting toxicities and treatment discontinuation. Visualization methods were explored and incorporated into interactive web-based research and patient-facing tools to enhance the interpretability and clinical utility of the TI.
conclusionIn conclusion, the TI is a useful summary measure that can be applied to a range of adverse event and patient-reported data to maximize the information collected and provide a more accurate and complete account of the tolerability experience. Future research will focus on extending applications of the TI and exploring its use for the design of clinical trials.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.