Nomogram Based on Liver Function Test Indicators for Survival Prediction in Nasopharyngeal Carcinoma Patients Receiving PD-1 Inhibitor Therapy
Bibliographic record
Abstract
Purpose: The aim of this study was to investigate the prognostic significance of PD-1 inhibitor therapy in nasopharyngeal carcinoma (NPC) and to develop a nomogram to estimate individual risks. Methods: We retrospectively analyzed 162 NPC patients who were administered the PD-1 inhibitor combined with radiotherapy and chemotherapy at the Sun Yat-Sen University Cancer Center. In total, 108 NPC patients were included in the training cohort and 54 NPC patients were included in the validation cohort. Univariate and multivariate Cox survival analyses were performed to determine the prognostic factors for 1-year and 2-year progression-free survival (PFS). In addition, a nomogram model was constructed to predict the survival probability of PFS. A consistency index (C-index), a decision curve, a clinical impact curve, and a standard curve were used to measure predictive accuracy, the clinical net benefit, and the consistency of prognostic factors. Results: Univariate and multivariate analyses indicated that the metastasis stage, the levels of ALT, the AST/ALT ratio, and the LDH were independent risk factors associated with the prognosis of PD-1 inhibitor therapy. A nomogram based on these four indicators was constructed and the Kaplan–Meier survival analysis showed that patients with a higher total score have a shorter PFS. The C-index of this model was 0.732 in the training cohort and 0.847 in the validation cohort, which are higher than those for the TNM stages (training cohort: 0.617; validation cohort: 0.727; p <0.05). Decision Curve Analysis (DCA), Net Reclassification Improvement (NRI), and Integrated Discrimination Improvement (IDI) showed that our model has better prediction accuracy than TNM staging. Conclusions: Predicting PFS in NPC patients based on liver function-related indicators before PD-1 treatment may help clinicians predict the efficacy of PD-1 treatment in these patients.
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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".