Low versus low-intermediate risk metastatic renal cell carcinoma (mRCC): Contemporary data from the International mRCC Database Consortium (IMDC).
Bibliographic record
Abstract
505 Background: The IMDC model has been effectively used to predict patients’ (pts) outcomes with mRCC, significantly guiding treatment decisions in the era of immune checkpoint inhibitors (ICIs) that have improved survival. In this study, we aim to characterize the clinical outcomes between patients classified as low (L, IMDC score of 0) vs. low-intermediate (L/I, IMDC score of 1) categories. Methods: Data of pts with mRCC receiving first-line (1L) ICI-based therapies with IMDC scores 0 or 1 was collected from the IMDC. Pts with score 1 were further subdivided into 4 groups based on their individual risk factor: low hemoglobin (Hb), Karnofsky Performance Status (KPS) <80, time from diagnosis (dx) to treatment < 1 year, and other risk factors including elevated neutrophils, platelets, and calcium. Overall survival (OS) and time to treatment failure (TTF) were analyzed using Cox regression models. Logistic regression was used to compare an objective response rate (ORR) according to RECIST 1.1. Results: Among the 803 eligible patients, 283 were classified as L and 520 as L/I. Patients' median age was 60 years (Q1-Q3: 23-88 years). The distribution of patients across specific risk categories within the IMDC score 1 group is detailed in the table. Compared to those with an IMDC score of 0, patients with a score of 1 related specifically to low performance status was associated with a shorter TTF (HR: 2.93, p<0.0001) and ORR (OR: 0.24, p=0.002). Anemia was significantly associated with decreased OS (HR: 1.61, p=0.002), shorter TTF (HR: 1.63, p=0.0002), and reduced ORR (OR: 0.65, p=0.05). Time from diagnosis to initiation of treatment within 1 year was significantly associated with shorter TTF (HR: 1.39, p=0.0015). Conclusions: Anemia and low-performance status emerged as the most informative factors differentiating prognosis between L and L/I IMDC risk groups receiving 1L ICI-based treatment. Molecular studies could further clarify these differences, aiding risk stratification and personalized treatment. Clinical outcomes of patients with mRCC based on risk factors. IMDC =0(N=283) IMDC=1 Low Hb(N=133) Time from dx to treatment <1 year (N=331) KPS <80 (N=21) Other risk factors (N=35) HR for OS* (95% CI) Ref. 1.61 (1.08-2.42)p-value = 0.002 1.11 (0.8-1.56)p-value = 0.55 1.9(0.819-4.408)p-value = 0.135 1.16 (0.55-2.42)p-value = 0.7 HR for TTF* (95% CI) Ref. 1.63 (1.26-2.10)p-value = 0.0002 1.39(1.13-1.7)p-value = 0.0015 2.88 (1.73-4.774)p-value <0.0001 1.9 (0.73-1.91)p-value = 0.47 OR for ORR** (95% CI) Ref. 0.65 (0.42-0.99)p-value = 0.05 1.1 (0.8-1.52)p-value = 0.52 0.22 (0.05-0.66)p-value = 0.02 0.99 (0.48 – 2)p-value = 0.98 *Analysis included 781 patients for OS and 778 for TTF after excluding cases with missing data. **78 not evaluable patients were included as non-responders.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| 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) | 0.002 | 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".