Progression-Free and Overall Survival of First-Line Treatments for Advanced Renal Cell Carcinoma: Indirect Comparison of Six Combination Regimens
1
Department of Pharmaceutical and Pharmacological Sciences, University of Padua, 35131 Padua, Italy
2
Hospital Pharmacy Department, University Hospital of Padua, 35128 Padua, Italy
3
Italian Society of Clinical Pharmacy and Therapeutics (SIFaCT), 10123 Turin, Italy
4
HTA Unit, Regional Health Service, 50139 Florence, Italy
5
Hospital Pharmacy, Vittorio Veneto Hospital, 31029 Vittorio Veneto, Italy
*
Author to whom correspondence should be addressed.
Cancers 2023, 15(7), 2029; https://doi.org/10.3390/cancers15072029
Submission received: 16 February 2023
/
Revised: 21 March 2023
/
Accepted: 28 March 2023
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Published: 29 March 2023
(This article belongs to the Special Issue Immune Checkpoint Inhibitors in the Treatment of Renal Cell Carcinoma)
Abstract
:Simple Summary
Recently, numerous treatments sharing similar mechanisms of action have been approved for advanced renal cell carcinoma. These combinations prolong survival compared to sunitinib, which was previously considered the standard of care in this context. Head-to-head comparisons between these innovative treatments are not available, but this information is needed to guide medical oncologists’ choices. To compare these combination therapies with one another and with sunitinib, our study used an innovative method (the Shiny method) that reconstructs individual patient data from published clinical trials. Using this approach, we demonstrated that pembrolizumab + lenvatinib is the most effective treatment in terms of progression-free survival (PFS) and overall survival (OS). Pembrolizumab + axitinib, nivolumab + cabozantinib and nivolumab + ipilimumab were similar in terms of PFS and superior to sunitinib, but pembrolizumab + axitinib also demonstrated a better OS. Our subgroup analysis showed that in favorable-risk patients, combination therapies showed no significant advantage over sunitinib, while in intermediate-poor risk patients, both pembrolizumab + axitinib and nivolumab + ipilimumab improved OS compared to sunitinib.
Abstract
Background: Recently, numerous combination therapies based on immune checkpoint inhibitors (ICI) and vascular endothelial growth factor (VEGF) inhibitors have been proposed as first-line treatments for advanced renal cell carcinoma (aRCC). Our study aimed to compare the efficacy of these combination regimens by the application of an innovative method that reconstructs individual patient data. Methods: Six phase III studies describing different combination regimens for aRCC were selected. Individual patient data were reconstructed from Kaplan–Meier (KM) curves through the “Shiny method”. Overall survival (OS) and progression-free survival (PFS) were compared among combination treatments and sunitinib. Results were summarized as multi-treatment KM curves. Standard statistical testing was used, including hazard ratio and likelihood ratio tests for heterogeneity. Results: In the overall population of aRCC patients, pembrolizumab + lenvatinib showed the longest median PFS and was expected to determine the longest OS. Pembrolizumab + axitinib, nivolumab + cabozantinib and nivolumab + ipilimumab were similar in terms of PFS, but pembrolizumab + axitinib also demonstrated a better OS. Our subgroup analysis showed that sunitinib is still a valuable option, whereas, in intermediate-poor risk patients, pembrolizumab + axitinib and nivolumab + ipilimumab significantly improve OS compared to sunitinib. Conclusion: The Shiny method allowed us to perform all head-to-head indirect comparisons between these agents in a context in which “real” comparative trials have not been performed.
1. Introduction
Over the past decades, systemic treatment for advanced renal cell carcinoma (aRCC) has considerably improved along with the development of new pharmacological targets. The main advancement in this setting has been the development of monoclonal antibodies and multitarget tyrosine-kinase inhibitors (TKI) that inhibit tumor growth and angiogenesis through the vascular endothelial growth factor (VEGF) pathway (e.g., bevacizumab, axitinib, lenvatinib, cabozantinib and sunitinib) [1].
Later on, inhibitors of immune checkpoints (ICIs), such as programmed cell death receptor-1 and its ligand (PD-1: nivolumab, pembrolizumab, PDL-1: atezolizumab and avelumab) and cytotoxic T lymphocyte-associated molecule-4 (CTLA-4; e.g., ipilimumab) have also demonstrated efficacy in aRCC [2,3].
While ICI were initially used as monotherapy after TKI, further evidence showed that combining these agents improved efficacy with an acceptable safety profile [3]. To date, combination regimens to treat aRCC include ICI/TKI (avelumab + axitinib, pembrolizumab + lenvatinib, nivolumab + cabozantinib and pembrolizumab + axitinib), ICI/anti-VEGF mAb (atezolizumab + bevacizumab) and a combination of two ICI (nivolumab + ipilimumab) [4,5].
In this ever-changing scenario, comparisons between these innovative treatments are essential to drivinge physician and regulatory authorities’ decisions; however, randomized clinical trials (RCTs) have tested the efficacy of combination treatments only against sunitinib. On the other hand, in the field of methods for survival analysis, a new artificial intelligence technique (called the “Shiny method”) has been developed and is increasingly used to reconstruct individual patient data from Kaplan-Meier (KM) curves and to generate cross-trial comparisons for which RCTs are lacking [6,7,8].
The Shiny method, also known as IPDfromKM, is an innovative tool of survival analysis in which software based on artificial intelligence reconstructs individual patient data. These reconstructed patients represent a new form of original clinical material; in particular, these reconstructed patients are suitable to perform indirect comparisons and consequently determine the place in the therapy of individual agents. In recent papers, we described the method and numerous experiences of application, especially in the field of oncology [9]. These analyses are helpful in providing an overview of new treatments, ranking their effectiveness based on indirect comparisons, and assessing equivalence from a regulatory viewpoint.
In this study, we applied the “Shiny method” to compare the efficacy of the main ICI-based combination regimens for aRCC, considering sunitinib as the standard of care (SOC).
2. Materials and Methods
2.1. Literature Search
First, we searched PubMed, Cochrane Library and the ClinicalTrials.gov databases to identify randomized controlled trials (RCTs) eligible for our analysis (last query on 30 October 2022). The search term was “[[advanced] or [metastatic]] and [[renal cell carcinoma] or [RCC]]”. The time interval was January 2019 to the present date. The selection of articles from our literature search was based on the PRISMA algorithm [10].
The main inclusion criteria were: (a) previously untreated adult patients with aRCC; (b) phase III trial; (c) PFS or OS endpoint; (d) results reported as a KM curve. For each curve of included trials, we collected the number of enrolled patients and the number of events (progression or death for PFS, death for OS). To avoid duplicate inclusion of patients of the same trial, we considered only the most recent publication.
2.2. Reconstruction of Individual Patient Data
We reconstructed patient-level data from the KM curves of treatment and control arms of each trial using the “Shiny method” [6,7,8]. For this purpose, the KM curves were digitized using Webplotdigitizer (version 4.5 online; https://apps.automeris.io/wpd/ (accessed on 15 February 2023)); then, the x-vs-y data points were input into the “Reconstruct individual patient data from Kaplan-Meier survival curve” function of the Shiny software (version: 1.2.2.0 online; last update: 1 April 2021); the total number of patients and events were input as well. In this way, we generated the reconstructed individual patient data for each arm of included RCTs. The reconstructed data of the patients are stored in archives containing the following information: (a) date of enrollment and last follow-up; the observation period of each patient results from the difference between these two dates. (b) patient outcome on the last follow-up date (alive, dead or censored).
As sunitinib was considered the SOC against which combination therapies were compared, patients receiving sunitinib monotherapy were pooled to form a single control group composed of patients from the control group of the 6 trials, namely IMmotion151 (n = 461), JAVELIN Renal 101 (n = 444), CheckMate 214 (n = 546), CLEAR (n = 357), CheckMate 9ER (n = 328) and KEYNOTE-426 (n = 429) trials [11,12,13,14,15,16].
2.3. Statistical Analysis
For each combination treatment, median PFS and OS were determined from reconstructed data and compared to sunitinib using Cox statistics for time-to-event end-points. We reported results as hazard ratio (HR) with a 95% confidence interval (95%CI). Indirect comparisons between treatments (in all head-to-head combinations) have been performed using the Cox model under the R-platform. Heterogeneity across control groups of different RCTs was quantified according to the likelihood ratio test and the concordance test. Statistical analyses were performed using the “survival” package under the R-platform (version 4.2.1) and SygmaPlot (version 13) software.
3. Results
3.1. Included Trials and Application of the Shiny Method
Six trials met the criteria for inclusion in our analysis (see Figure 1 for the PRISMA flowchart and Table 1 for RCT characteristics).
In our analysis of PFS based on these trials, 12 patient cohorts, along with their respective information on progressions, were reconstructed from the original Kaplan-Meier curves through the Shiny method. Then, the Kaplan-Meier PFS curves from these reconstructed patients were plotted individually and reported in a single multi-treatment graph (Figure 2A), which is the typical result generated by the Shiny method. In this graph, the 6 cohorts treated with sunitinib were pooled into a single cohort, thus generating a total of 7 curves. The same analysis was then performed for OS. The latter results are reported in Figure 2B. Detailed results of all head-to-head comparisons are reported in Table 2 and Figure S2.
3.2. Progression-Free Survival: Indirect Comparisons of the Six Combination Treatments Plus Sunitinib with One Another
In analyzing our results on PFS, the six combination treatments, along with sunitinib monotherapy, were ranked as follows:
- pembrolizumab + lenvatinib: median PFS 24.52 months (95%CI 22.02 to 29.5); this combination treatment is significantly better than all other combination treatments, in particular of nivolumab + cabozantinib, which ranks second, with HR = 0.714 (95%CI 0.574 to 0.889);
- nivolumab + cabozantinib: median PFS 17.12 months (13.01 to 20.2);
- pembrolizumab + axitinib: median PFS 16.99 months (14.21 to 21.1);
- nivolumab + ipilimumab: median PFS 14.29 months (12.02 to 18.8); these three combinations produced similar gains of survival with respect to sunitinib (see Supplementary Table S1), with no difference in the head-to-head comparisons; in contrast, they were significantly superior to atezolizumab + bevacizumab and numerically superior to avelumab + axitinib;
- avelumab + axitinib: median PFS 13.85 months (95%CI 10.99 to 16.7) was inferior to all other combinations except atezolizumab + bevacizumab (HR = 0.817, 95%CI 0.678 to 0.985);
- atezolizumab + bevacizumab: median PFS 11.45 months (95%CI 9.87 to 13.5) was significantly inferior to all other treatments, and it does not produce any significant gain of function compared to sunitinib (HR = 0.9822, 95%CI 0.8637 to 1.117).
- sunitinib (6 control arms pooled together): median PFS 9.92 months (95%CI 9.53 to 10.09) was inferior to 5 out of six combination treatments, with the exception of atezolizumab + bevacizumab.
Forest plots of HRs with 95%CI for PFS of the six trials against pooled sunitinib controls are shown in Figure S1.
3.3. Overall Survival: Indirect Comparisons of the 6 Combination Treatments Plus Sunitinib with One Another
In analyzing our results on OS, the six combination treatments, along with sunitinib monotherapy, were ranked as follows:
- pembrolizumab + lenvatinib: median OS not reached, but this treatment is expected to rank first based on the HR analysis vs. sunitinib (HR = 0.57, 95%CI 0.45 to 0.72); in the head-to head comparison, pembrolizumab + lenvatinib was numerically superior to both pembrolizumab + axitinib (HR = 0.868, 95%CI 0.634 to 1.189) and nivolumab + ipilimumab (HR = 0.781, 95%CI 0.592 to 1.031) but significantly better than other combinations.
- pembrolizumab + axitinib: median OS not reached, but this treatment is expected to rank second based on the HR analysis vs. sunitinib (HR = 0.6601, 95%CI 0.5369 to 0.8116); in the head-to head comparison, pembrolizumab + axitinib was numerically superior to nivolumab + ipilimumab, nivolumab + cabozantinib and avelumab + axitinib and significantly superior to atezolizumab + bevacizumab;
- nivolumab + ipilimumab: median OS 59.2 months (48 to 70.3). This treatment was numerically superior to nivolumab + cabozantinib and avelumab + axitinib;
- nivolumab + cabozantinib: median OS 37.9 months (95%CI 36.3 to NA). This combination failed to demonstrate any significant advantage compared to other treatments but it was numerically superior to atezolizumab + bevacizumab and almost similar to avelumab + axitinib;
- avelumab + axitinib: median OS not reached. This treatment was numerically superior only to atezolizumab + bevacizumab and sunitinib monotherapy;
- sunitinib (6 control arms pooled together): median OS 41.2 months (95%CI 35.6 to 46.5) was inferior to 5 out of six combination treatments, with the exception of atezolizumab + bevacizumab;
- atezolizumab + bevacizumab: median OS 35.5 months (95%CI 28.9 to NA). This treatment was significantly worse than most of the comparators, including sunitinib monotherapy. The HR analysis vs. sunitinib failed to demonstrate a significant gain in survival (HR = 1.0818, 95%CI 0.9148 to 1.2794).
3.4. Heterogeneity Analysis on Sunitinib Monotherapy Curves
Figure 3A,B shows the curves of PFS and OS obtained from the 6 control groups treated with sunitinib monotherapy that were compared for heterogeneity assessment. As controls should behave in a similar way, if heterogeneity is present, this may be due to differences in baseline patients’ characteristics across the 6 trials. The results indicated that heterogeneity was present among the six trials both according to the likelihood ratio test and the concordance test applied to PFS (likelihood test = 50.06 with 5 df; p < 0.001; concordance, 0.552, SE = 0.007) and OS (likelihood test = 15.36 with 5 df; p = 0.009; concordance, 0.534, SE = 0.01. The presence of heterogeneity is driven mainly by the nivolumab + ipilimumab and lenvatinib + pembrolizumab RCT control arm, respectively, in the PFS and OS analysis.
In the case of PFS, there is no longer a significant heterogeneity when the nivolumab + ipilimumab control group is left out (likelihood ratio test = 8.86 on 4 df, p = 0.06); this demonstrates that in this case, the heterogeneity is driven mainly by this control arm.
In contrast, in the case of OS analysis, there is still significant heterogeneity after excluding the nivolumab + ipilimumab control group (likelihood ratio test = 14.6 on 4 df, p = 0.006). In this case, the lenvatinib + pembrolizumab control arm performed significantly better than the others, and so the heterogeneity was driven by this curve in the OS analysis. As expected, the likelihood ratio test after excluding the lenvatinib + pembrolizumab control group was not significant (likelihood ratio test = 3.56 on 4 df, p = 0.5).
3.5. Subgroup Analysis: Overall Survival in Favourable vs. Intermediate/Poor Risk Patients
In patients treated with nivolumab + ipilimumab and pembrolizumab + axitinib, OS’s KM curves were available for patients with favourable versus intermediate/poor risk.
Multi-treatment KM curves are depicted in Figure 4A,B.
In patients with favourable risk, median OS values of nivolumab + ipilimumab and pembrolizumab + axitinib do not significantly differ from sunitinib group (HR = 1.026, 95%CI 0.6398 to 1.4866 for nivolumab + ipilimumab and HR = 1.024, 95%CI 0.5500 to 1.735 for pembrolizumab + lenvatinib axitinib vs. sunitinib). The head-to-head comparisons do not show any difference between the two combination treatments.
In the intermediate-poor risk group, sunitinib performed significantly worse than combination regimens (median OS 29.4 months, 95%CI 25.4–34.3). Nivolumab + ipilimumab (HR = 1.437, 95%CI 0.5872 to 0.8247) improve OS compared to sunitinib monotherapy similarly to pembrolizumab + axitinib (HR = 1.579, 95%CI 0.5011 to 0.8001). The head-to-head comparison between these combinations do not show any difference (HR = 0.91, 95%CI 0.682 to 1.215).
4. Discussion
The present study investigated the main first-line combination treatments for aRCC by application of an innovative method of indirect comparison of survival data, the “Shiny method”. Our choice to employ this approach to conduct these indirect comparisons, not a standard network meta-analysis [17,18,19], was because this method offers some advantages, such as considering the length of the follow-up of the trials and managing in a more precise way the variance of the model. The fact that the Shiny method evaluates not only the number of events but also the time of their occurrence is particularly important in a context like the one studied in here, where the follow-up lengths were considerably different across the agents investigated, and some differences were substantial. For example, some treatments (such as nivolumab + ipilimumab or sunitinib monotherapy and, to a lesser extent, lenvatinib + pembrolizumab and nivolumab + cabozantinib) had a particularly long follow-up as opposed to atezolizumab + bevacizumab, the follow-up of which was short. Consequently, some event rates were influenced by the length of the follow-up; in this framework, the rankings estimated by the Shiny method have an advantage in that they accounted for this important factor.
In recent years, the Shiny method has increasingly been used not only in oncology but also in other areas of of therapeutics, such as medical devices [20], surgery [21,22] and also in patients with COVID-19 [23]. However, oncology and oncohematology remain the two main areas of application, where the Shiny method represents a quite simple alternative to network meta-analysis [8,9,24,25].
Although combination regimens for aRCC target similar pathways, our results indicate that their efficacy is not equal. Median PFS and OS obtained with atezolizumab + bevacizumab did not differ significantly from that obtained with sunitinib, and so this result does not yet justify its use. In contrast, several combinations of TKI + ICI demonstrated a significant advantage, in terms of both PFS and OS, when compared to sunitinib monotherapy, in particular pembrolizumab + lenvatinib. Long-term follow-up will tell whether this therapy will confirm its superiority compared to the other combinations.
Pembrolizumab + axitinib, nivolumab + cabozantinib and nivolumab + ipilimumab were similar in terms of PFS but pembrolizumab + axitinib demonstrated a better OS.
In subgroup analysis, patients with favourable risk obtained excellent results in terms of OS also with sunitinib monotherapy, and so combination therapy in these patients seems to add little OS benefit. In contrast, the intermediate/poor risk group of patients seems to benefit mostly from combination therapy, though we found no difference between nivolumab + ipilimumab vs. pembrolizumab + axitinib. In intermediate/poor risk patients, no separate KM curves were reported for patients with intermediate/low risk treated with pembrolizumab + lenvatinib, and this prevented us from applying the Shiny method to test the superiority observed by Bosma et al. in their meta-analysis [17].
Although the criteria for patient selection were similar among the six studies, our heterogeneity analysis of control arms demonstrated a significantly better PFS and OS in the controls of the CheckMate214 trial (the one testing nivolumab + ipilimumab) compared with the other control arms. Hence, this raises the possibility that the remarkable survival found in the active arm of CheckMate214 depends on the favorable characteristics of the patients and is therefore an overestimate. To further assess this issue, we compared in more detail the inclusion criteria and the characteristics of patients in the selected RCTs, but we found no remarkable difference. Of note, CheckMate214 did not report the Karnofsky performance status score (PS) of patients, while the CLEAR trial presented a slightly higher number of patients with favorable MSKCC prognostic score and with better PS.
In the light of our results, at least three combination therapies seem to have the best therapeutic profile. In the clinical use, the selection of the most suitable treatment should be guided by the patient’s characteristics, particularly, the fitness of the subject to tolerate the adverse drug reactions (ADR), combined with a foresight on the best sequence of treatments if progression occurs [26]. Nivolumab + ipilimumab is burdened by more intense immune-related ADRs, while lenvatinib + pembrolizumab is characterized by a higher incidence of grade >3 ADR (82.4% of patients) than other TKI + ICI combinations [27]. Although ADR may impact on health-related quality of life (HRQOL), a recent study observed that patients treated with pembrolizumab + lenvatinib have similar HRQOL score than patients receiving sunitinib [28]. It would be worthwhile to extend the comparison of HRQOL scores to the combination regimens, evaluated in the present study in terms of OS and PFS.
The use of these combination treatments in real practice may generate further evidence to guide treatment selection. For example, a recent study investigating the efficacy of nivolumab + ipilimumab vs. pembrolizumab + axitinib in real practice showed a reduced PFS compared with that reported in the RCTs [29].
5. Conclusions
In conclusion, the “Shiny method” permitted to generate valuable clinical results on new treatments for aRCC and to discuss their efficacy on the basis of original indirect comparisons. In addition, the “one to many approach”, recently developed by our group, will allow us to quickly update the results of the present analysis as new treatments or longer follow-up will become available [30].
Supplementary Materials
The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/cancers15072029/s1, Table S1: Comparison of PFS and OS between combination treatments and sunitinib; Figure S1: Forest plots of HRs with 95%CI for PFS and OS of the six trials against pooled sunitinib controls; Figure S2: Visual representation of indirect treatment comparisons for PFS; Figure S3: Visual representation of indirect treatment comparisons for OS.
Author Contributions
Conceptualization, A.M. and V.D.; methodology, A.M.; software, A.M.; validation, A.M.; formal analysis, A.O. and V.D.; investigation, A.O. and V.D.; data curation, A.O. and V.D.; writing—original draft preparation, A.O. and V.D.; writing—review and editing, A.M. and D.M.; supervision, A.M. and D.M.; project administration, M.C. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
The data presented in this study are available in the article and in the supplementary material.
Acknowledgments
Italian Society for Clinical Pharmacy and Therapeutics (SIFaCT), Turin, Italy.
Conflicts of Interest
The authors declare no conflict of interest.
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Figure 1.
PRISMA flowchart of the process of trial selection. Renal cell carcinoma (RCC); Progression-free survival (PFS).
Figure 1.
PRISMA flowchart of the process of trial selection. Renal cell carcinoma (RCC); Progression-free survival (PFS).
Figure 2.
Application of the Shiny method to sunitinib monotherapy (n = 2565 from 6 trials; in red) and to 6 combination treatments: (a) atezolizumab 1200 mg + bevacizumab 15 mg/kg (n = 454; in gold); (b) avelumab 10 mg/kg + axitinib 5 mg (n = 442; in green); (c) nivolumab 3 mg/kg + ipilimumab 1 mg/kg (n = 550; in light green); (d) lenvatinib 20 mg + pembrolizumab 200 mg (n = 355; in light blue); (e) nivolumab 240 mg + cabozantinib 40 mg (n = 323; in purple); (f) and pembrolizumab 200 mg + axitinib 5 mg (n = 432; in pink); (g) sunitinib monotherapy 50 mg (n = 2565; in red). n: number of enrolled patients. End-point: (A) progression-free survival (PFS), (B) Overall survival (OS). Time in months.
Figure 2.
Application of the Shiny method to sunitinib monotherapy (n = 2565 from 6 trials; in red) and to 6 combination treatments: (a) atezolizumab 1200 mg + bevacizumab 15 mg/kg (n = 454; in gold); (b) avelumab 10 mg/kg + axitinib 5 mg (n = 442; in green); (c) nivolumab 3 mg/kg + ipilimumab 1 mg/kg (n = 550; in light green); (d) lenvatinib 20 mg + pembrolizumab 200 mg (n = 355; in light blue); (e) nivolumab 240 mg + cabozantinib 40 mg (n = 323; in purple); (f) and pembrolizumab 200 mg + axitinib 5 mg (n = 432; in pink); (g) sunitinib monotherapy 50 mg (n = 2565; in red). n: number of enrolled patients. End-point: (A) progression-free survival (PFS), (B) Overall survival (OS). Time in months.
Figure 3.
After reconstruction of individual patient data from control arms of included trials (sunitinib monotherapy 50 mg), the following Kaplan-Meier curves were generated from: Rini et al., 2021 (n = 461; in red [11]); Choueiri et al., 2020 (n = 444; in gold [12]); Motzer et al., 2022 (n = 546; in green [13]); Motzer et al., 2021 (n = 357; in light blue [14]); Motzer et al., 2022 (n = 328; in blue [15]); Powles et al., 2020 (n = 355; in purple [16]). (A) progression-free survival (PFS), (B) Overall survival (OS). Time in months.
Figure 3.
After reconstruction of individual patient data from control arms of included trials (sunitinib monotherapy 50 mg), the following Kaplan-Meier curves were generated from: Rini et al., 2021 (n = 461; in red [11]); Choueiri et al., 2020 (n = 444; in gold [12]); Motzer et al., 2022 (n = 546; in green [13]); Motzer et al., 2021 (n = 357; in light blue [14]); Motzer et al., 2022 (n = 328; in blue [15]); Powles et al., 2020 (n = 355; in purple [16]). (A) progression-free survival (PFS), (B) Overall survival (OS). Time in months.
Figure 4.
Overall survival Subgroups analysis. (A) In favourable-risk patients; application of the Shiny method to sunitinib monotherapy (n = 243 from 2 trials; in red) and to 2 combination treatments: (a) nivolumab 3 mg/kg + ipilimumab 1 mg/kg (n = 120; in green) and (b) pembrolizumab 200 mg + axitinib 5 mg (n = 138; in blue). (B) In intermediate-risk/poor-risk patients; Application of the Shiny method to sunitinib monotherapy (n = 731 from 2 trials; in red) and to 2 combination treatments: (a) nivolumab 3 mg/kg + ipilimumab 1 mg/kg (n = 430; in green) and (b) pembrolizumab 200 mg + axitinib 5 mg (n = 294; in blue). n: number of enrolled patients. End-point: overall survival (OS), Time in months.
Figure 4.
Overall survival Subgroups analysis. (A) In favourable-risk patients; application of the Shiny method to sunitinib monotherapy (n = 243 from 2 trials; in red) and to 2 combination treatments: (a) nivolumab 3 mg/kg + ipilimumab 1 mg/kg (n = 120; in green) and (b) pembrolizumab 200 mg + axitinib 5 mg (n = 138; in blue). (B) In intermediate-risk/poor-risk patients; Application of the Shiny method to sunitinib monotherapy (n = 731 from 2 trials; in red) and to 2 combination treatments: (a) nivolumab 3 mg/kg + ipilimumab 1 mg/kg (n = 430; in green) and (b) pembrolizumab 200 mg + axitinib 5 mg (n = 294; in blue). n: number of enrolled patients. End-point: overall survival (OS), Time in months.
Table 1.
Main information about the 6 RCTs included in the analysis.
| PFS | OS | ||||||
|---|---|---|---|---|---|---|---|
| # | Trial | Reference | Treatments under Comparison | Treatment Group (Events/ Patients) | Controls (Events/ Patients) | Treatment Group (Events/ Patients) | Controls (Events/ Patients) |
| RCC1 | IMmotion151 trial (two-arm) | Rini et al. [11] | atezolizumab (1200 mg) + bevacizumab (15 mg/kg) intravenously, every 3 weeks; | 283/454 | 309/461 | 194/454 | 192/461 |
| sunitinib (50 mg) orally once daily for 4 weeks (6 weeks cycle). | |||||||
| RCC2 | JAVELIN Renal 101 Trial (two-arm) | Choueiri et al. [12] | avelumab (10 mg/kg) intravenously, every 2 weeks + axitinib (5 mg) orally twice daily; | 242/442 | 336/444 | 109/442 | 129/444 |
| sunitinib (50 mg) orally once daily for 4 weeks (6 weeks cycle). | |||||||
| RCC3 | CheckMate 214 Trial (two-arm) | Motzer et al. [13] | nivolumab (3 mg/kg) + ipilimumab (1 mg/kg) every 3 weeks for four cycles; | 266/550 | 358/546 | 297/550 | 339/546 |
| sunitinib (50 mg) orally once daily for 4 weeks (6 weeks cycle). | |||||||
| RCC4 | CLEAR Trial (three-arm) § | Motzer et al. [14] | lenvatinib (20 mg) orally once daily + pembrolizumab (200 mg) intravenously, every 3 weeks; | 160/355 | 205/357 | 80/355 | 105/357 |
| sunitinib (50 mg) orally once daily for 4 weeks (6 weeks cycle). | |||||||
| RCC5 | CheckMate 9ER Trial (two-arm) | Motzer et al. [15] | nivolumab (240 mg) intravenously, every 2 weeks + cabozantinib (40 mg) orally once daily; | 206/323 | 223/328 | 121/323 | 150/328 |
| sunitinib (50 mg) orally once daily for 4 weeks (6 weeks cycle). | |||||||
| RCC6 | KEYNOTE-426 Trial (two-arm) | Powles et al. [16] | pembrolizumab (200 mg) intravenously every 3 weeks (35 cycles) + axitinib (5 mg) orally twice daily; | 264/432 | 281/429 | 142/432 | 178/429 |
| sunitinib (50 mg) orally once daily for 4 weeks (6 weeks cycle). | |||||||
All values of event number were explicitly reported in the original trials or relative Supplementary Materials; events were then calculated as the difference of the total number of patients minus the total number of censored cases. § CLEAR included an arm treated with lenvatinib (18 mg orally once daily) + everolimus (5 mg orally once daily), which has not been included in our analysis.
Table 2.
Results of statistical analysis of indirect treatment comparison of PFS between combination regimens.
Table 2.
Results of statistical analysis of indirect treatment comparison of PFS between combination regimens.
| HR | Lower 0.95 | Upper 0.95 | |
|---|---|---|---|
| atezolizumab + bevacizumab vs. avelumab + axitinib | 1.223 | 1.015 | 1.474 |
| atezolizumab + bevacizumab vs. nivolumab + ipilimumab | 1.462 | 1.227 | 1.743 |
| atezolizumab + bevacizumab vs. pembrolizumab + lenvatinib | 1.981 | 1.611 | 2.435 |
| atezolizumab + bevacizumab vs. nivolumab + cabozantinib | 1.415 | 1.163 | 1.721 |
| atezolizumab + bevacizumab vs. pembrolizumab + axitinib | 1.401 | 1.165 | 1.685 |
| avelumab + axitinib vs. atezolizumab + bevacizumab | 0.817 | 0.678 | 0.985 |
| avelumab + axitinib vs. nivolumab + ipilimumab | 1.195 | 0.998 | 1.432 |
| avelumab + axitinib vs. pembrolizumab + lenvatinib | 1.619 | 1.311 | 1.999 |
| avelumab + axitinib vs. nivolumab + cabozantinib | 1.156 | 0.946 | 1.413 |
| avelumab + axitinib vs. pembrolizumab + axitinib | 1.145 | 0.948 | 1.384 |
| nivolumab + ipilimumab vs. atezolizumab + bevacizumab | 0.684 | 0.574 | 0.815 |
| nivolumab + ipilimumab vs. avelumab + axitinib | 0.837 | 0.698 | 1.002 |
| nivolumab + ipilimumab vs. pembrolizumab + lenvatinib | 1.355 | 1.108 | 1.657 |
| nivolumab + ipilimumab vs. nivolumab + cabozantinib | 0.968 | 0.800 | 1.170 |
| nivolumab + ipilimumab vs. pembrolizumab + axitinib | 0.958 | 0.802 | 1.145 |
| pembrolizumab + lenvatinib vs. atezolizumab + bevacizumab | 0.505 | 0.411 | 0.621 |
| pembrolizumab + lenvatinib vs. avelumab + axitinib | 0.618 | 0.500 | 0.763 |
| pembrolizumab + lenvatinib vs. nivolumab + ipilimumab | 0.738 | 0.604 | 0.903 |
| pembrolizumab + lenvatinib vs. nivolumab + cabozantinib | 0.714 | 0.574 | 0.889 |
| pembrolizumab + lenvatinib vs. pembrolizumab + axitinib | 0.707 | 0.574 | 0.872 |
| nivolumab + cabozantinib vs. atezolizumab + bevacizumab | 0.707 | 0.581 | 0.860 |
| nivolumab + cabozantinib vs. avelumab + axitinib | 0.865 | 0.708 | 1.057 |
| nivolumab + cabozantinib vs. nivolumab + ipilimumab | 1.033 | 0.854 | 1.250 |
| nivolumab + cabozantinib vs. pembrolizumab + lenvatinib | 1.400 | 1.125 | 1.743 |
| nivolumab + cabozantinib vs. pembrolizumab + axitinib | 0.990 | 0.812 | 1.208 |
| pembrolizumab + axitinib vs. atezolizumab + bevacizumab | 0.714 | 0.594 | 0.858 |
| pembrolizumab + axitinib vs. avelumab + axitinib | 0.873 | 0.723 | 1.055 |
| pembrolizumab + axitinib vs. nivolumab + ipilimumab | 1.043 | 0.873 | 1.247 |
| pembrolizumab + axitinib vs. pembrolizumab + lenvatinib | 1.414 | 1.147 | 1.742 |
| pembrolizumab + axitinib vs. nivolumab + cabozantinib | 1.010 | 0.828 | 1.231 |
Table 3.
Results of statistical analysis of indirect treatment comparison of OS between combination regimens.
Table 3.
Results of statistical analysis of indirect treatment comparison of OS between combination regimens.
| HR | Lower 0.95 | Upper 0.95 | |
|---|---|---|---|
| atezolizumab + bevacizumab vs. avelumab + axitinib | 1.263 | 0.97 | 1.645 |
| atezolizumab + bevacizumab vs. nivolumab + ipilimumab | 1.474 | 1.181 | 1.840 |
| atezolizumab + bevacizumab vs. pembrolizumab + lenvatinib | 1.888 | 1.412 | 2.523 |
| atezolizumab + bevacizumab vs. nivolumab + cabozantinib | 1.270 | 0.976 | 1.654 |
| atezolizumab + bevacizumab vs. pembrolizumab + axitinib | 1.639 | 1.256 | 2.138 |
| avelumab + axitinib vs. atezolizumab + bevacizumab | 0.791 | 0.608 | 1.030 |
| avelumab + axitinib vs. nivolumab + ipilimumab | 1.167 | 0.909 | 1.498 |
| avelumab + axitinib vs. pembrolizumab + lenvatinib | 1.494 | 1.093 | 2.042 |
| avelumab + axitinib vs. nivolumab + cabozantinib | 1.005 | 0.754 | 1.341 |
| avelumab + axitinib vs. pembrolizumab + axitinib | 1.297 | 0.970 | 1.734 |
| nivolumab + ipilimumab vs. atezolizumab + bevacizumab | 0.678 | 0.543 | 0.847 |
| nivolumab + ipilimumab vs. avelumab + axitinib | 0.857 | 0.667 | 1.1 |
| nivolumab + ipilimumab vs. pembrolizumab + lenvatinib | 1.28 | 0.970 | 1.690 |
| nivolumab + ipilimumab vs. nivolumab + cabozantinib | 0.862 | 0.671 | 1.106 |
| nivolumab + ipilimumab vs. pembrolizumab + axitinib | 1.112 | 0.864 | 1.431 |
| pembrolizumab + lenvatinib vs. atezolizumab + bevacizumab | 0.530 | 0.396 | 0.708 |
| pembrolizumab + lenvatinib vs. avelumab + axitinib | 0.669 | 0.490 | 0.915 |
| pembrolizumab + lenvatinib vs. nivolumab + ipilimumab | 0.781 | 0.592 | 1.031 |
| pembrolizumab + lenvatinib vs. nivolumab + cabozantinib | 0.673 | 0.492 | 0.920 |
| pembrolizumab + lenvatinib vs. pembrolizumab + axitinib | 0.868 | 0.634 | 1.189 |
| nivolumab + cabozantinib vs. atezolizumab + bevacizumab | 0.787 | 0.605 | 1.025 |
| nivolumab + cabozantinib vs. avelumab + axitinib | 0.995 | 0.746 | 1.327 |
| nivolumab + cabozantinib vs. nivolumab + ipilimumab | 1.161 | 0.904 | 1.490 |
| nivolumab + cabozantinib vs. pembrolizumab + lenvatinib | 1.486 | 1.087 | 2.031 |
| nivolumab + cabozantinib vs. pembrolizumab + axitinib | 1.29 | 0.965 | 1.724 |
| pembrolizumab + axitinib vs. atezolizumab + bevacizumab | 0.61 | 0.468 | 0.796 |
| pembrolizumab + axitinib vs. avelumab + axitinib | 0.771 | 0.577 | 1.03 |
| pembrolizumab + axitinib vs. nivolumab + ipilimumab | 0.9 | 0.699 | 1.158 |
| pembrolizumab + axitinib vs. pembrolizumab + lenvatinib | 1.152 | 0.841 | 1.577 |
| pembrolizumab + axitinib vs. nivolumab + cabozantinib | 0.775 | 0.58 | 1.036 |
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Ossato, A.; Mengato, D.; Chiumente, M.; Messori, A.; Damuzzo, V. Progression-Free and Overall Survival of First-Line Treatments for Advanced Renal Cell Carcinoma: Indirect Comparison of Six Combination Regimens. Cancers 2023, 15, 2029. https://doi.org/10.3390/cancers15072029
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Ossato A, Mengato D, Chiumente M, Messori A, Damuzzo V. Progression-Free and Overall Survival of First-Line Treatments for Advanced Renal Cell Carcinoma: Indirect Comparison of Six Combination Regimens. Cancers. 2023; 15(7):2029. https://doi.org/10.3390/cancers15072029
Chicago/Turabian StyleOssato, Andrea, Daniele Mengato, Marco Chiumente, Andrea Messori, and Vera Damuzzo. 2023. "Progression-Free and Overall Survival of First-Line Treatments for Advanced Renal Cell Carcinoma: Indirect Comparison of Six Combination Regimens" Cancers 15, no. 7: 2029. https://doi.org/10.3390/cancers15072029
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