The role of nephrectomy in metastatic renal cell carcinoma in the immuno‐oncology era
Notice bibliographique
Résumé
Three first-line, randomised phase III trials (Checkmate 214 [1], Checkmate 9ER [2], and Keynote 426 [3]) relied on predefined statistical criteria to validate the survival advantage of immuno-oncology (IO)-based systemic treatment in metastatic RCC (mRCC) relative to sunitinib. Within each of these three trials, stratification according to prior nephrectomy was addressed in post hoc progression-free survival (PFS) and overall survival (OS) analyses. We focussed on these three post hoc analyses in addition to illustrating the effect of prior nephrectomy in the pivotal sunitinib vs interferon trial (Motzer et al. [4]) for comparison purpose [1-4]. The rates of prior nephrectomy varied across trials. In Keynote 426, the prior nephrectomy rate was 83% (treatment-arm, pembrolizumab/axitinib) vs 84% (control-arm, sunitinib) [3]. In Checkmate 9ER, prior nephrectomy rate was 69% (treatment-arm, nivolumab/cabozantinib) vs 41.5% (control-arm, sunitinib) [2]. In Checkmate 214, prior nephrectomy rate was 82% (treatment-arm, nivolumab/ipilimumab) vs 80% (control-arm, sunitinib) [1]. The proportions of favourable-, intermediate- and poor-risk patients also varied across trials. In the prior nephrectomy cohort of Keynote 426, the proportions of intermediate- or poor-risk patients ranged from 63.5% (treatment-arm) to 64% (control-arm) [3]. In the cohort of Keynote 426 without prior nephrectomy, the proportions of intermediate- or poor-risk patients were even higher (90% in the treatment arm and 96% in the control-arm) [3]. In Checkmate 214 and Checkmate 9ER, no detailed information on risk proportions according to nephrectomy status was available [1, 2]. In Checkmate 9ER, across cohorts with and without prior nephrectomy, proportions of intermediate- or poor-risk patients were 77% (treatment) vs 78% (control) [2]. In Checkmate 214, across cohorts with and without prior nephrectomy, proportions of intermediate- or poor-risk patients were 77% and 77%, respectively [1]. Regarding PFS, prior nephrectomy status was associated with longer PFS in Checkmate 9ER [2] (ratio of hazards ratios [rHR] 0.73) and Checkmate 214 [1] (HR 0.90), but not in Keynote 426 [3] (HR 1.03). For comparison, in the pivotal sunitinib vs interferon trial, prior nephrectomy status was also associated with longer PFS (HR 0.71) [4]. Regarding OS, prior nephrectomy status was associated with longer OS only in Checkmate 9ER [2], but not in Checkmate 214 [1] or in Keynote 426 [3] (Fig. 1). The above observations suggest more favourable PFS in prior nephrectomy patients in two of the three IO trials. Lack of PFS benefit in Keynote 426 [3] may be related to high proportion of intermediate- or poor-risk patients in the prior nephrectomy arm in addition to the smallest proportion of patients without prior nephrectomy of all three trials. Indirectly, the highest proportion of prior nephrectomy patients in Keynote 426 [3] endorses the use of nephrectomy in the setting examined within this trial. Nonetheless, further post hoc analyses, especially, those from the CLEAR trial (ClinicalTrials.gov Identifier: NCT02811861) should ideally complement our observations [5]. Finally, our observations should be interpreted in the light of their non-randomised design. Therefore, the beneficial effect of prior nephrectomy on PFS should be interpreted as a mere association and not causation. Furthermore, it should also be emphasised that prior nephrectomy status indicates the use of nephrectomy at non-metastatic stage in most patients. Consequently, it cannot be interpreted as synonymous with cytoreductive nephrectomy. Nevertheless, even after taking into account these considerations, it appears likely that the role of nephrectomy in the management of mRCC will persist also in the era of IO treatment. However, ideal patient selection and timing of nephrectomy in patients with mRCC treated with IO regimens is currently unclear. In this regard, future guideline recommendations on the role of nephrectomy in the IO era will eventually be shaped by the results of several ongoing prospective randomised trials (NCT03055013, NCT02210117, NCT03288532, NCT03138512, NCT03142334, NCT03024996). Open access funding enabled and organized by Projekt DEAL. The authors declare no disclosure of interest.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».