Impact of family history of prostate cancer on disease progression for prostatic cancer patients undergoing active surveillance: A systematic review and meta-analysis
Bibliographic record
Abstract
PURPOSE: To evaluate how a family history of prostate cancer influences the progression of the disease in individuals with prostate cancer undergoing active surveillance. MATERIALS AND METHODS: We conducted a thorough literature search in PubMed/MEDLINE, Embase, and Cochrane Library up to June 2023. This systematic review was registered in PROSPERO (CRD42023441853). The study evaluated the effects of family history of prostate cancer (intervention) on disease progression (outcome) in prostate cancer patients undergoing active surveillance (population) and compared them to those without a family history (comparators). For time to disease progression outcomes, the extracted data were synthesized using the inverse variance method on the log hazard ratios scale. RESULTS: A total of eight studies were incorporated into this systematic review and meta-analysis. The combined hazard ratio for unadjusted disease progression was 1.06 (95% confidential interval [CI] 0.66-1.69; p=0.82). The combined hazard ratio for adjusted disease progression was 1.31 (95% CI 1.16-1.48; p<0.0001). All the enlisted studies demonstrated high quality based on the Newcastle-Ottawa scale. The certainty of evidence for univariate and multivariate analysis of disease progression was very low and low, respectively. Publication bias for all studies was not significant. CONCLUSIONS: For individuals with prostate cancer opting for active surveillance, a family history of prostate cancer may serve as an independent risk factor associated with an elevated risk of disease progression. Clinicians should be counseled about the increased risk of disease progression in patients with a family history of prostate cancer undergoing active surveillance.
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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 | 0.013 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.037 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".