Genetic biomarkers associated with changes in quality of life and pain following palliative radiotherapy in patients with bone metastases
Bibliographic record
Abstract
BACKGROUND: Patients with bone metastases undergoing palliative radiation therapy (RT) may experience changes in both the functional and symptomatic aspects of quality of life (QOL). The European Organization of Cancer Research and Treatment (EORTC) QOL Questionnaire Core-15 Palliative (QLQ-C15-PAL) is a validated questionnaire employed to assess QOL specifically in palliative patients. Our study aimed to identify single-nucleotide variant (SNV) genetic biomarkers associated with changes in QOL and pain. METHODS: Fifty-two patients who received a single 8-Gy RT for painful bone metastases completed the EORTC QOL-C15-PAL questionnaire prior to randomization and at 42-day post RT. Saliva samples obtained at day of RT were sequenced, and SNVs from genes involved in inflammation, radiation response, immune response, DNA damage, or QOL were assessed for association with changes in global QOL or the pain scale items using the Cochran-Armitage trend test. The penalized LASSO method with minimum Bayesian information criterion was used to select a multi-SNV model out of significant SNVs (P<0.005) and to produce prognostic scores for patients that categorized them into risk groups of low, middle, and high. RESULTS: The multivariable model predicting global QOL included 14 SNVs, of which HS1BP3 rs35579164 G:C and ABCA1 rs2230805 C>T had the largest positive and negative effect sizes, respectively (HS1BP3: 8.21, ABCA1: -3.44). The model for the response of QOL pain item included 8 SNVs, of which PLAUR rs4760 A>G and ELAC2rs11545302 had the largest positive and negative effect sizes, respectively (PLAUR: 5.23; ELAC: -3.84). The patients' risk groups were highly predictive of QOL response (P<0.0001) and pain item response (P<0.0001). In logistic regression analysis accounting for baseline factors of gender and primary cancer site, the global QOL risk group predicts pain response after RT [OR: 2.1, 95% confidence interval (CI): 1.2-3.9, P=0.015], but the QOL pain item risk group did not (OR: 0.93; 95% CI: 0.5-1.6, P=0.79). The multi-SNVs model included SNVs from genes involved in metabolism, membrane transport, cell cycle control, ciliary structure, and gene expression regulation. CONCLUSIONS: SNVs were significantly associated with changes in global QOL of global domain and pain item in patients with bone metastases. Identification of genetic biomarkers predictive of QOL items may allow patients and health care providers anticipate and better address the needs of the palliative cancer patient population.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".