Survival rates with external beam radiation therapy in newly diagnosed elderly metastatic prostate cancer patients
Bibliographic record
Abstract
BACKGROUND: The survival benefit of primary external beam radiation therapy (EBRT) has never been formally tested in elderly men who were newly diagnosed with metastatic prostate cancer (mPCa). We hypothesized that elderly patients may not benefit of EBRT to the extent as younger newly diagnosed mPCa patients, due to shorter life expectancy. METHODS: We relied on Surveillance, Epidemiology and End Results (2004-2016) to identify elderly newly diagnosed mPCa patients, aged >75 years. Kaplan-Meier, univariable and multivariable Cox regression models, as well as Competing Risks Regression models tested the effect of EBRT versus no EBRT on overall mortality (OM) and cancer-specific mortality (CSM). RESULTS: Of 6556 patients, 1105 received EBRT (16.9%). M1b stage was predominant in both EBRT (n = 823; 74.5%) and no EBRT (n = 3908; 71.7%, p = 0.06) groups, followed by M1c (n = 211; 19.1% vs. n = 1042; 19.1%, p = 1) and M1a (n = 29; 2.6% vs. n = 268; 4.9%, p < 0.01). Median overall survival (OS) was 23 months for EBRT and 23 months for no EBRT (hazard ratio [HR]: 0.97, p = 0.6). Similarly, median cancer-specific survival (CSS) was 29 months for EBRT versus 30 months for no EBRT (HR: 1.04, p = 0.4). After additional multivariable adjustment, EBRT was not associated with lower OM or lower CSM in the entire cohort, as well as after stratification for M1b and M1c substages. CONCLUSIONS: In elderly men who were newly diagnosed with mPCa, EBRT does not affect OS or CSS. In consequence, our findings question the added value of local EBRT in elderly newly diagnosed mPCa patients.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".