Social determinants of health (SDOH) and survival among patients with metastatic prostate cancer (mPC): A systematic literature review (SLR).
Bibliographic record
Abstract
25 Background: Population level data show strong associations between race and other SDOH including income, education, and geographic region of residence. The relationship between SDOH and clinical outcomes has become increasingly recognized. This review examines the impact of SDOH on survival in patients with mPC in real-world (RW) settings. Methods: A systematic literature search in accordance with Cochrane guidelines was conducted on July 7, 2022, searching for RW studies published as full-text (Jan 2012-July 2022) and conferences (Jan 2019-July 2022) using Ovid MEDLINE, Embase, and Cochrane. A manual search of key congress websites for conference abstracts was also conducted. Studies which assessed the impact of SDOHs on survival, treatment access, and other clinical outcomes in patients with mPC were included in the overall SLR. Here, we present results from studies which assessed the impact of SDOH on overall survival (OS) and prostate cancer specific mortality (PCSM). Clinical trials were excluded. Results: Of 3,228 records screened, 86 studies were included, with findings reported in 67 full-text publications (60 US and 7 ex-US) and 28 conference abstracts (22 US and 6 ex-US). The impact of race on survival was reported in 54 studies. While most studies showed no difference between Black vs White for both OS (n=22) and PCSM (n=8), for patients on specific mPC treatments, there was an association between Black race and improved OS (n=5). Asian patients had improved OS vs White patients (n=4), and reduced PCSM vs White (n=6) and Black patients (n=1). Higher income was generally associated with improved OS (n=7), but no difference in PCSM (n=3). Although the regions compared differed, most studies found disparities in OS among US geographic regions (n=5). Education level was generally not associated with OS (n=2) or PCSM (n=3). Most studies showed that married patients had improved OS (n=4) and reduced PCSM (n=3) compared to unmarried patients. Conclusions: This SLR demonstrated that various SDOH are associated with disparities in survival among mPC patients. Asian race, which is generally associated with higher frequency of better SDOH risk factors, was linked with better OS. In contrast, Black race, which is generally associated with higher frequency of worse SDOH risk factors, was associated with similar or better OS. Having lower income and being unmarried were both associated with reduced OS, while disparities in OS were reported across geographic regions of the US. More studies are needed to understand why SDOH are linked with poor outcomes, including their connection with access to 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 | 0.009 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.010 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".