A Study of Peripheral Blood Parameters to Predict Response to Induction Chemotherapy and Overall Survival in Advanced Laryngeal Squamous Cell Carcinoma
Bibliographic record
Abstract
PURPOSE: the purpose of this study was to screen peripheral blood parameters and construct models predicting the prognosis and induction chemotherapy (IC) response in locally advanced laryngeal squamous cell carcinoma (LSCC) patients. METHODS: A total of 128 stage III/IVa LSCC patients (who required a total laryngectomy) were enrolled in a retrospective study from January 2013 to September 2020 at Beijing Tongren Hospital of Capital Medical University. Among them, 62 patients received IC (IC group), and 66 patients immediately underwent a total laryngectomy (TL) after diagnosis (surgery group). Demographic information and peripheral blood parameters were collected for further analysis. The overall survival (OS), progression-free survival (PFS), and disease-specific survival (DSS) were compared between the two groups. The prognosis and survival were also compared between patients with laryngeal function preservation (LFP) and those with TL. RESULTS: The Receiver Operating Characteristic (ROC) curve for IC response in the IC group showed that the AUC of the blood model based on the four peripheral blood parameters of fibrinogen (FIB), platelet (PLT), high-density lipoprotein cholesterol (HDL), and albumin (ALB) was significantly higher than the TNM stage model's AUC (0.7932 vs. 0.6568). We constructed a nomogram blood model to predict IC response (C-Index = 0.793). Regarding the OS of all patients, an ROC analysis for overall survival, the Kaplan-Meier (K-M) method with a log-rank test, and multivariate analysis indicated age, clinical stage, FIB, and hemoglobin (HGB) were independent prognostic factors for the OS of LSCC patients. The blood-clinical logistic model (AUC = 0.7979) was constructed based on the four prognosis factors, which were superior to the blood (AUC = 0.6867) or clinical models (AUC = 0.7145) alone to predict OS. We constructed a nomogram model based on age, clinical stage, FIB, and HGB to predict OS for LSCC patients (C-Index = 0.792). Besides this, there were no significant differences in OS, PFS, and DSS between IC and surgery groups or LFP and TL groups. CONCLUSION: Peripheral blood parameters help predict IC response and overall survival. Furthermore, induction chemotherapy significantly improves laryngeal function preservation without lowering the survival prognosis.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".