Marital Status, Living Arrangement, and Survival among Individuals with Advanced Prostate Cancer in the International Registry for Men with Advanced Prostate Cancer
Bibliographic record
Abstract
BACKGROUND: Studies have shown improved survival among individuals with cancer with higher levels of social support. Few studies have investigated social support and overall survival (OS) in individuals with advanced prostate cancer in an international cohort. We investigated the associations of marital status and living arrangements with OS among individuals with advanced prostate cancer in the International Registry for Men with Advanced Prostate Cancer (IRONMAN). METHODS: IRONMAN is enrolling participants diagnosed with advanced prostate cancer (metastatic hormone-sensitive prostate cancer, mHSPC; castration-resistant prostate cancer, CRPC) from 16 countries. Participants in this analysis were recruited between July 2017 and January 2023. Adjusting for demographics and tumor characteristics, the associations were estimated using Cox regression and stratified by disease state (mHSPC, CRPC), age (<70, ≥70 years), and continent of enrollment (North America, Europe, Other). RESULTS: We included 2,119 participants with advanced prostate cancer, of whom 427 died during up to 5 years of follow-up (median 6 months). Two-thirds had mHSPC. Most were married/in a civil partnership (79%) and 6% were widowed. Very few married participants were living alone (1%), while most unmarried participants were living alone (70%). Married participants had better OS than unmarried participants [adjusted HR: 1.44; 95% confidence interval (CI): 1.02-2.02]. Widowed participants had the worst survival compared with married individuals (adjusted HR: 1.89; 95% CI: 1.22-2.94). CONCLUSIONS: Among those with advanced prostate cancer, unmarried and widowed participants had worse OS compared with married participants. IMPACT: This research highlighted the importance of social support in OS within this vulnerable population.
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.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".