Impact of the systemic immune-inflammation index for the prediction of prognosis and modification of the risk model in patients with metastatic renal cell carcinoma treated with first-line tyrosine kinase inhibitors
Bibliographic record
Abstract
INTRODUCTION: International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) criteria are the most representative risk model for patients with metastatic renal cell carcinoma (mRCC). However, the intermediate-risk group of IMDC criteria is thought to include patients with different prognoses because many of the patients are classified into the intermediate-risk group. In this study, we investigated the impact of systemic immune-inflammation index (SII), which is calculated based on neutrophil count, platelet count, and lymphocyte count, on predicting the prognosis in patients with mRCC, and its usefulness for re-classification of patients with a more sophisticated risk model. METHODS: From January 2008 to January 2018, 179 mRCC patients with a pretreatment and SII were retrospectively investigated. All patients were classified into either a high-SII group or a low-SII group based on the cutoff value of a SII at 730, as reported in previous studies; the overall survival (OS) rates in each group were compared. RESULTS: The median age was 65 years old. Males and females comprised 145 and 34 cases, respectively. The categories of favorable-, intermediate-, and poor-risk groups in the IMDC model were assessed in 39, 102, and 38 cases, respectively. The median observation period was 24 months. The low-SII and high-SII groups consisted of 73 and 106 cases, respectively. The 50% OS in the high-SII group was 21.4 months, which was significantly worse than that in the low-SII group (49.7 months; p<0.0001). Multivariate analysis showed that a high SII was an independent predictive factor for a worse OS. Next, we constructed a modified IMDC risk model that included the SII instead of a neutrophil count and a platelet count. By using this modified IMDC model, all cases were re-classified into four groups of 33, 52, 81, and 13 cases with 50% OS of 88.8, 45.9, 29.4, and 4.8 months, respectively. CONCLUSIONS: The SII is useful for establishing a more sophisticated prognostic model that can stratify mRCC patients into four groups with different prognoses.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".