Abstract
Afatinib is an effective therapy for metastatic non-small cell lung cancer (NSCLC) but it is associated with a relatively high incidence of severe diarrhea. The association between pre-treatment candidate predictors (age, sex, race, performance status, renal function, hemoglobin, and measures of body mass) and severe (grade ≥ 3) diarrhea was evaluated using logistic regression with pooled individual participant data from seven clinical studies. A risk score was developed based on the count of major risk factors. Overall, 184 of 1151 participants (16%) experienced severe diarrhea with use of afatinib. Body weight, body mass index, and body surface area all exhibited a prominent non-linear association where risk increased markedly at the lower range (p < 0.005). Low weight (<45 kg), female sex, and older age (≥60 years) were identified as major independent risk factors (p < 0.01). Each risk factor was associated with a two-fold increase in the odds of severe diarrhea, and this was consistent between individuals commenced on 40 mg or 50 mg afatinib. A simple risk score based on the count of these risk factors identifies individuals at lowest and highest risk (C-statistic of 0.65). Risk of severe diarrhea for individuals commenced on 40 mg afatinib ranged from 6% for individuals with no risk factors to 33% for individuals with all three risk factors.
Original language | English |
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Article number | 384 |
Number of pages | 10 |
Journal | Cancers |
Volume | 10 |
Issue number | 10 |
DOIs | |
Publication status | Published - 15 Oct 2018 |
Bibliographical note
(CC-BY 4.0) Open Access article licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license (http://creativecommons.org/licenses/by/4.0).Keywords
- EGFR inhibitor
- diarrhea
- toxicity
- prediction model
- adverse event
- Afatinib
- Toxicity
- Prediction model
- Adverse event
- Diarrhea