Clinical benefit in oncology trials: Is this a patient-centered or tumor-centered endpoint?
Bibliographic record
Abstract
6564 Background: Clinical benefit (CB) was first successfully used as an endpoint in 1997 in the pivotal study of gemcitabine in advanced pancreas cancer. In the trial by Burris et al (J Clin Oncol. 1997) CB was a composite measure of pain, performance status, and weight. Here we describe how CB has been used in oncology trials since that time. Methods: We performed an electronic search ( www.jco.org ) for reports of all clinical trials (phase I, II, III) published in the Journal of Clinical Oncology 1997–2008 citing ‘clinical benefit.‘ Eligible trials were those reporting clinical benefit as an endpoint. Details related to study methodology, sponsorship, and endpoints were abstracted. Use of CB was classified as patient-centered if it referred to improvement in the clinical parameters used by Burris et al or in other disease-related symptoms. CB was classified as tumor-centered if it related to objective tumor criteria for partial/complete response and/or stable disease. Descriptive statistics were used to summarize findings and the chi-square test used to compare proportions. Results: 71 trials reporting CB as an endpoint were identified: 37 in breast, 8 in pancreas, and 26 in other cancers. The definition of CB was patient-centered in 21 trials (30%) and tumor-centered in 50 trials (70%). Only 20% (14/71) of trials (including all 8 pancreas studies) used the original Burris definition. In the second half of the study period there was an increase in the number of trials using CB as an endpoint (17 to 54 trials) and in the proportion of trials with a tumor-centered definition (10/17, 59% to 41/54, 76%, p = 0.09). Study variables associated with the use of a tumor-centered definition include: disease site (breast 35/37, 95%; all others 16/34, 47%, p < 0.001) and intervention (hormone or targeted agent 38/40, 95%; chemotherapy 13/31, 42%, p < 0.001). There was no association with sponsorship (industry 41/56, 73%; non-industry 10/15, 67%, p = 0.86) or phase of trial (phase I/II 36/48, 75%; phase III 15/23, 65%, p = 0.56). Conclusions: Despite its initial definition, clinical benefit is often used to describe objective tumor findings. Clinical trials should use endpoints in a consistent manner to enable clear communication between investigators, clinicians, and patients about the benefit of novel therapies. No significant financial relationships to disclose.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.425 | 0.559 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".