Prognostic factors versus predictive factors: Examples from a clinical trial of erlotinib

It would be helpful to have factors that could identify patients who will, or will not, benefit from treatment with specific therapies. Ideally, these should be molecular-based factors. When results with molecular-based factors are disappointing, physicians often use clinical characteristics to make...

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Bibliographic Details
Published in:Molecular oncology 2008-04, Vol.1 (4), p.406-412
Main Author: Clark, Gary M.
Format: Article
Language:English
Subjects:
Biomarkers
Cancer therapies
Carcinoma, Non-Small-Cell Lung - diagnosis
Carcinoma, Non-Small-Cell Lung - drug therapy
Carcinoma, Non-Small-Cell Lung - mortality
Carcinoma, Non-Small-Cell Lung - pathology
Cigarettes
Clinical trials
Confidence intervals
Drug Delivery Systems
Epidermal growth factor
Epidermal growth factor receptor
ErbB Receptors - antagonists & inhibitors
Erlotinib
Erlotinib Hydrochloride
Females
Gender
Histology
Humans
Hypothesis testing
Lung cancer
Males
Medical prognosis
Mutation
Non-small lung cancer
Patients
Predictive
Predictive Value of Tests
Prognosis
Prognostic
Quinazolines - therapeutic use
Randomized Controlled Trials as Topic
Response rates
Retrospective Studies
Smoking
Smoking - adverse effects
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Summary:It would be helpful to have factors that could identify patients who will, or will not, benefit from treatment with specific therapies. Ideally, these should be molecular-based factors. When results with molecular-based factors are disappointing, physicians often use clinical characteristics to make treatment decisions. Several characteristics have been suggested to predict sensitivity to epidermal growth factor receptor inhibitors in patients with non-small lung cancer, including gender, histology, smoking history. This report demonstrates that gender and histology are actually prognostic, rather than predictive factors. Before biomarkers or clinical characteristics are included in guidelines for selecting patients for specific treatments, it is imperative that the prognostic effects of these factors are distinguished from their ability to predict a differential clinical benefit from the specific treatment.
ISSN:1574-7891
1878-0261
DOI:10.1016/j.molonc.2007.12.001