ArticleStatistics in medicine2021
On the properties of the toxicity index and its statistical efficiency.
Article in Statistics in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Feasibility of frequent monitoring of symptoms using the PRO-CTCAE in the NRG-BR004 clinical trial.JNCI cancer spectrum · 2025Trial
- Article
- The CHRONO trial: Protocol for a randomized controlled trial of early time-restricted eating in patients with breast or rectal cancer.Nutrition research (New York, N.Y.) · 2026Article
- Analyses of adverse events and patient-reported outcomes with the toxicity index in cancer clinical trials.Cancer · 2025Review
- Combining Response and Toxicity Data to Implement Project Optimus.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2024Article
- Reply to S. Zhang et al and S. Selukar.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2024Article
- Development of a Web-Based Interactive Tool for Visualizing Breast Cancer Clinical Trial Tolerability Data.JCO clinical cancer informatics · 2024Article
- Importance of Low- and Moderate-Grade Adverse Events in Patients' Treatment Experience and Treatment Discontinuation: An Analysis of the E1912 Trial.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2024Article
- The Weighted Toxicity Score: Confirmation of a Simple Metric to Communicate Toxicity in Randomized Trials of Systemic Cancer Therapy.The oncologist · 2024Article
- A toolbox of different approaches to analyze and present PRO-CTCAE data in oncology studies.Journal of the National Cancer Institute · 2023Article
- Article
- Simulation study comparing analytical methods for single-item longitudinal patient-reported outcomes data.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2023Article
- Randomized clinical trial of tissue equivalent bolus prescription in postmastectomy radiotherapy stratified by skin involvement status.Clinical and translational radiation oncology · 2023Article
- Toxicity Index, patient-reported outcomes, and persistence of breast cancer chemotherapy-associated side effects in NRG Oncology/NSABP B-30.NPJ breast cancer · 2022Article
- Evaluating Treatment Tolerability Using the Toxicity Index With Patient-Reported Outcomes Data.Journal of pain and symptom management · 2022Article
- Evaluating the Association of Adverse Events and Patient-Reported Symptoms to Endocrine Therapy Tolerability.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2022Article
- Toxicity Index, Patient-Reported Outcomes, and Early Discontinuation of Endocrine Therapy for Breast Cancer Risk Reduction in NRG Oncology/NSABP B-35.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2021Article
- Applying the Toxicity Index to Patient-Reported Symptom Data: An Example Using the European Organization for Research and Treatment of Cancer Colorectal Cancer-Specific Quality of Life Questionnaire.Clinical therapeutics · 2021Article
- On the properties of the toxicity index and its statistical efficiency.Statistics in medicine · 2021Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Cancer clinical trials typically generate detailed patient toxicity data. The most common measure used to summarize patient toxicity is the maximum grade among all toxicities and it does not fully represent the toxicity burden experienced by patients. In this article, we study the mathematical and statistical properties of the toxicity index (TI), in an effort to address this deficiency. We introduce a total ordering, (T-rank), that allows us to fully rank the patients according to how frequently they exhibit toxicities, and show that TI is the only measure that preserves the T-rank among its competitors. Moreover, we propose a Poisson-Limit model for sparse toxicity data. Under this model, we develop a general two-sample test, which can be applied to any summary measure for detecting differences among two population of toxicity data. We derive the asymptotic power function of this class as well as the asymptotic relative efficiency (ARE) of the members of the class. We evaluate the ARE formula empirically and show that if the data are drawn from a random Poisson-Limit model, the TI is more efficient, with high probability, than the maximum and the average summary measures. Finally, we evaluate our method on clinical trial toxicity data and show that TI has a higher power in detecting the differences in toxicity profile among treatments. The results of this article can be applied beyond toxicity modeling, to any problem where one observes a sparse array of scores on subjects and a ranking based on extreme scores is desirable.
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