Evaluation of New Treatments in Radiation Oncology
Are They Better Than Standard Treatments?
- Heloisa P. Soares, MD;
- Ambuj Kumar, MD, MPH;
- Stephanie Daniels, RN, MPH;
- Suzanne Swann, PhD;
- Alan Cantor, PhD;
- Iztok Hozo, PhD;
- Mike Clark, DPhil;
- Fadila Serdarevic, MD, MPH;
- Clement Gwede, RN, PhD;
- Andy Trotti, MD;
- Benjamin Djulbegovic, MD, PhD
- Author Affiliations: H. Lee Moffitt Cancer Center & Research Institute at University of South Florida, Tampa (Drs Soares, Kumar, Cantor, Serdarevic, Gwede, Trotti, and Djulbegovic and Ms Daniels); Department of Statistics, Radiation Therapy Oncology Group, Philadelphia, Pa (Dr Swann); Department of Mathematics, University of Indiana Northwest, Gary (Dr Hozo); UK Cochrane Centre, Oxford, England (Dr Clark).
- Corresponding Author: Benjamin Djulbegovic, MD, PhD, H. Lee Moffitt Cancer Center &@ Research Institute at the University of South Florida, Department of Interdisciplinary Oncology, 12902 Magnolia Dr, SRB 4, Room 24031, Tampa, FL 33612 (djulbebm{at}moffitt.usf.edu).
Abstract
Context The superiority of innovative over standard treatments is not known. To describe accurately the outcomes of innovations that are tested in randomized controlled trials (RCTs) 3 factors have to be considered: publication rate, quality of trials, and the choice of the adequate comparator intervention.
Objective To determine the success rate of innovative treatments by assessing preferences between experimental and standard treatments according to original investigators’ conclusions, determining the proportion of RCTs that achieved primary outcomes’ statistical significance, and performing meta-analysis to examine if the summary point estimate favored innovative vs standard treatments.
Data Sources Randomized controlled trials conducted by the Radiation Therapy Oncology Group (RTOG).
Study Selection All completed phase 3 trials conducted by the RTOG since its creation in 1968 until 2002. For multiple publications of the same study, we used the one with the most complete primary outcomes and with the longest follow-up information.
Data Extraction We used the US National Cancer Institute definition of completed studies to determine the publication rate. We extracted data related to publication status, methodological quality, and treatment comparisons. One investigator extracted the data from all studies and 2 independent investigators extracted randomly about 50% of the data. Disagreements were resolved by consensus during a meeting.
Data Synthesis Data on 12 734 patients from 57 trials were evaluated. The publication rate was 95%. The quality of trials was high. We found no evidence of inappropriateness of the choice of comparator. Although the investigators judged that standard treatments were preferred in 71% of the comparisons, when data were meta-analyzed innovations were as likely as standard treatments to be successful (odds ratio for survival, 1.01; 99% confidence interval, 0.96-1.07; P = .5). In contrast, treatment-related mortality was worse with innovations (odds ratio, 1.76; 99% confidence interval, 1.01-3.07; P = .008). We found no predictable pattern of treatment successes in oncology: sometimes innovative treatments are better than the standard ones and vice versa; in most cases there were no substantive differences between experimental and conventional treatments.
Conclusion The finding that the results in individual trials cannot be predicted in advance indicates that the system and rationale for RCTs is well preserved and that successful interventions can only be identified after an RCT is completed.
