Serum Lactate Dehydrogenase Is Prognostic for Survival in Patients with Bone Metastases from Breast Cancer: A Retrospective Analysis in Bisphosphonate-Treated Patients
Bibliographic record
Abstract
PURPOSE: Survival is highly variable in women with bone metastases from breast cancer and prognostic factors are needed. We analyzed data from a phase III trial comparing zoledronic acid (ZOL) with pamidronate in patients with breast cancer and bone metastases to identify variables prognostic for overall survival. EXPERIMENTAL DESIGN: Patients who received ZOL (n = 435) with bone marker assessments and complete baseline data were included. Relative risks (RR) of death over 24 months were assessed using a stratified Cox regression analysis. A reduced model was generated using stepwise backward elimination until only significant (P < 0.05) variables remained. RESULTS: Only 5 of 19 variables analyzed remained significantly prognostic for survival in the reduced multivariate model. These included age more than 50 years (RR 1.78-2.53, P ≤ 0.01 for each decade >50 versus ≤ 50); Functional Assessment of Cancer Therapy-General (FACT-G) score less than 65 units (P < 0.05 vs. ≥ 75 units); impaired (PS ≥ 1) versus fully active (PS = 0) Eastern Cooperative Oncology Group (ECOG) performance status (RR 1.74, P < 0.01); prior versus no prior chemotherapy (RR 1.97; P < 0.01), and lactate dehydrogenase (LDH) levels. Lactate dehydrogenase ≥ upper limit of normal (ULN) but < 2 × ULN correlated with a two-fold increased risk of death, and LDH > 2 × ULN correlated with a six-fold increased risk of death versus LDH < ULN (P < 0.0001 for both). Baseline bone marker levels were not significantly correlated with survival after adjustment for other significant covariates. CONCLUSIONS: This retrospective analysis shows that LDH levels correlate strongly with survival in patients with bone metastases from breast cancer and confirms the relevance of previously described prognostic factors.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".