A Review and Meta-Analysis of Prostate Cancer Utilities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Health-related quality of life is a key issue in prostate cancer (PC) management. The authors summarized published utilities for common health-related quality of life outcomes of PC and determined how methodological factors affect them. METHODS: In their systematic review, the authors identified 23 articles in English, providing 173 unique utilities for PC health states, each obtained from 2 to 422 respondents. Data were pooled using linear mixed-effects modeling with utilities clustered within the study, weighted by the number of respondents divided by the variance of each utility. RESULTS: In the base model, the estimated utility of the reference case (scenario of a metastatic PC patient with severe sexual symptoms, rated by non-PC patients using time tradeoff) was 0.76. Disease stage, symptom type and severity, source of utility, and scaling method were associated with utility differences of 0.10 to 0.32 (P < 0.05). Utilities from PC patients rating their own health were 0.14 higher than those from the reference case, but utilities from PC patients rating scenarios were lowest. Time tradeoff yielded the highest utilities. Computer administration yielded lower utilities than personal interview (P = 0.02). Neither the scale's high anchor nor study purpose had significant effects on utilities. CONCLUSIONS: This study provides pooled utility estimates for common PC health states and describes how clinical and methodological factors can significantly affect these values. When possible, utility estimates for a modeling application should be derived similarly. Formal data synthesis methods might be useful to researchers integrating utility data from heterogeneous sources. Further exploration of these methods for this purpose is warranted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.043 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.014 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 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 it