Impact of body mass index (BMI) on treatment outcomes to immune checkpoint blockade (ICB) in metastatic renal cell carcinoma (mRCC).
Bibliographic record
Abstract
566 Background: An elevated BMI is associated with improved survival in mRCC patients treated with oral targeted therapies (TT); however, this relationship in the contemporary treatment landscape is unknown. We investigated the effect of BMI on outcomes in mRCC patients treated with PD-1/PD-L1 ICB. Methods: We analyzed 147 patients with mRCC who received ICB alone or in combination with VEGF or other therapies. The association of BMI with objective response rate (ORR), progression-free survival (PFS), and overall survival (OS) was evaluated using logistic and Cox regression models, adjusted for known prognostic factors including International Metastatic RCC Database Consortium (IMDC) risk groups, line of therapy, ECOG (0 vs ≥1), and histology. Results: Median follow up was 25.5 (4.3-78.6) months (mos). Median time on ICB was 5.1 ( < 0.1-69.7) mos. Overall, most patients were male (71%), had clear cell histology (85%), and were intermediate risk (60%). 43% received first-line ICB and 45% received ICB in combination therapy (37% with VEGF inhibition, 8% with other therapies). At ICB initiation, 46 (31%) patients were considered underweight/normal weight (BMI < 25 kg/m2), 56 (38%) overweight (BMI 25-30 kg/m2), and 45 (31%) obese (BMI > 30 kg/m2). Patients with high BMI (≥ 25) had improved OS (median 34.3 vs 16.7 mos, 2-yr OS 61 vs 42%, p = 0.016) compared to those with low BMI ( < 25), with an adjusted hazard ratio (HR) = 0.74 (0.44-1.26). ORR (33 vs 28%, p = 0.7) and PFS (median 8.2 vs 5.9 mos, p = 0.4) did not statistically differ. Patients who experienced a BMI change from ≥ 25 at start of first-line TT to < 25 at start of subsequent-line ICB displayed shorter OS (adjusted HR = 2.25 (0.94-5.35)) compared to those with no change. Conclusions: High BMI appears to be associated with improved OS in mRCC patients treated with ICB. This contemporary data is consistent with the “obesity paradox” demonstrated in the TT era. Validation with the IMDC database and examination of underlying mechanisms are ongoing.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".