A Systematic Review of Heterogeneity in Outcome Definition and Reporting in Localised Renal Cancer
Bibliographic record
Abstract
Context: Outcomes in renal cell carcinoma (RCC) are reported inconsistently, with variability in definitions and measurement. Hence, it is difficult to compare intervention effectiveness and synthesise outcomes for systematic reviews and to create clinical practice guidelines. This uncertainty in the evidence makes it difficult to guide patient-clinician decision-making. One solution is a core outcome set (COS): an agreed minimum set of outcomes. Objective: To describe outcome reporting, definitions, and measurement heterogeneity as the first stage in co-creating a COS for localised renal cancer. Evidence acquisition: We systematically reviewed outcome reporting heterogeneity in effectiveness trials and observational studies in localised RCC. In total, 2822 studies (randomised controlled trials, cohort studies, case-control studies, systematic reviews) up to June 2020 meeting our inclusion criteria were identified. Abstracts and full texts were screened independently by two reviewers; in cases of disagreement, a third reviewer arbitrated. Data extractions were double-checked. Evidence synthesis: We included 149 studies and found that there was inconsistency in which outcomes were reported across studies and variability in the definitions used for outcomes that were conceptually the same. We structured our analysis using the outcome classification taxonomy proposed by Dodd et al. Outcomes linked to adverse events (eg, bleeding, outcomes linked to surgery) and renal injury outcomes (reduced renal function) were reported most commonly. Outcomes related to deaths from any cause and from cancer were reported in 44% and 25% of studies, respectively, although the time point for measurement and the analysis methods were inconsistent. Outcomes linked to life impact (eg, global quality of life) were reported least often. Clinician-reported outcomes are more frequently reported than patient-reported outcomes in the renal cancer literature. Conclusions: This systematic review underscores the heterogeneity of outcome reporting, definitions, and measurement in research on localised renal cancer. It catalogues the variety of outcomes and serves as a first step towards the development of a COS for localised renal cancer. Patient summary: We reviewed studies on localised kidney cancer and found that multiple terms and definitions have been used to describe outcomes. These are not defined consistently, and often not defined at all. Our review is the first phase in developing a core outcome set to allow better comparisons of studies to improve medical care.
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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 | 0.176 | 0.495 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.015 |
| Bibliometrics | 0.024 | 0.024 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".