The Effects of Second Primary Malignancies and Frailty on Overall Survival and Mortality in Geriatric Turkish Patients with Multiple Myeloma
Bibliographic record
Abstract
The study aims to investigate second primary malignancy (SPM) development and frailty in Turkish geriatric patients with multiple myeloma (MM) and to assess the relationship between overall survival (OS) and various characteristics including SPM and frailty. Seventy-two patients diagnosed with and treated for MM were enrolled in the study. Frailty was determined by the IMWG Frailty Score. Fifty-three participants (73.6%) were found to have clinically-relevant frailty. Seven patients (9.7%) had SPM. Median follow-up was 36.5 (22–48.5) months, and 17 patients died during the follow-up period. Overall (OS) was 49.40 (45.01–53.80) months. Shorter OS was found in patients with SPM (35.29 (19.66–50.91) months) compared to those without (51.05 (46.7–55.4) months) (Kaplan–Meier; p = 0.018). The multivariate cox proportional hazards model revealed that patients with SPM had 4.420-fold higher risk of death than those without (HR: 4.420, 95% CI: 1.371–14.246, p = 0.013). Higher ALT levels were also independently associated with mortality (p = 0.038). The prevalence of SPM and frailty was high in elderly patients with MM in our study. The development of SPM independently reduces survival in MM; however, frailty was not found to be independently associated with survival. Our results suggest the importance of individualized approaches in the management of patients with MM, particularly with regard to SPM development.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".