High-dose interleukin2 – a 10-year single-site experience in the treatment of metastatic renal cell carcinoma: careful selection of patients gives an excellent outcome
Bibliographic record
Abstract
Background VEGF-targeted therapy has become the mainstay of treatment for majority of mRCC patients. For most patients, benefit is short-lived and therefore treatment remains palliative in intent. HD IL2 is an effective immunotherapy treatment capable of durable remission in some patients but its unselected use has been difficult due to its modest response rate and considerable adverse effects. Using set pathology criteria as a selection tool in clinical practice, we have been able to show improved outcomes in our previous report. Here, we present an updated and extended report of this treatment and seek to explore any pathological, clinical and treatment variables likely to predict better outcomes. Methods This is an extension of a previously reported clinical audit, which includes mRCC cases treated with HD IL2 between 2003 and 2013. Since 2006, tumour specimens of potential candidates were routinely reviewed prospectively and stratified into Favourable or Other categories based on constitution of histological growth pattern, namely alveolar or solid versus papillary and/or sarcomatoid architecture; clear cell versus granular cell cytoplasmic morphology. HD IL2 was preferentially offered to patients with Favourable pathology. Outcome evaluation includes response rates, survival, and treatment tolerance. Multivariate analysis was performed to explore potential prognostic and predictive factors. Results Among prospectively selected patients with Favourable pathology (n = 106), overall response rate was 48.1 % (51/106) with CR rate of 21.6 % (23/106). Median OS was 58.1 months. Factors associated with significantly better response and/or survival includes favourable pathology pattern, higher cycle 1 tolerance and lower number of metastatic organ sites (<3). CAIX (Carbonic anhydrase 9) has prognostic value but is not predictive of response. Toxicities were those expected of IL2 but were manageable on general medical wards, with no treatment-related death. Importantly most complete responses were durable with 76 % (23/30) cases remained relapse-free (median 39 months follow up) and 2 of the seven who relapsed had had long-term disease free survival after resection of oligometastatic relapse. Conclusions Our experience shows that HD IL2 remains an effective and safe treatment in well-selected cases of mRCC. The result in this single-institution patient series confirms similar outcomes to our previously reported retrospective series. Given the prospect of long-term remission, fit patients with Favourable histology and low disease burden should be considered for HD IL2 in an experienced centre. Better understanding has been gained from this in-depth analysis especially the examination of possible response predictors and strategies that can improve treatment outcome.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".