Abstract
Background
Combinations of checkpoint inhibitors and tyrosine kinase inhibitors are contemporary standards of care in first-line treatment of patients with advanced renal cell carcinoma. Real-world evidence remains scarce.
Patients and methods
We retrospectively investigated the tolerability and effectiveness of lenvatinib plus pembrolizumab—approved based on the results of the CLEAR trial—under real-world conditions in 145 patients.
Results
The median age was 63 years (range 21-87 years). The majority of patients were male (69%) and had a predominant clear-cell histology (88%). Adverse events (AEs) occurred in 94% of patients, with fatigue (50%), hypertension (39%) and diarrhea (38%) as most common AEs. Grade ≥3 AEs were seen in 59%. Interruption of at least one of the drugs due to toxicities was required in 68% of patients. The dose of lenvatinib was reduced in 56%. The objective response rate was 66%, with 8% of patients achieving a complete remission. Primary progression was seen in 8% of patients. At a median follow-up time of 12.2 months [95% confidence interval (CI) 10.3-15.5 months], 35% of patients experienced disease progression. Progression-free survival at 6 months was 76% (95% CI 71.9% to 79.7%). Twenty-one percent of patients died, most of them due to progressive disease. Limitations of our analysis are the short follow-up period and the retrospective nature of the analyses.
Conclusions
Our cohort supports the use of lenvatinib plus pembrolizumab in a real-world population, including CLEAR-ineligible patients. However, AEs should be closely monitored and treatment should be adapted accordingly.
Key words: advanced renal cell carcinoma, lenvatinib, pembrolizumab, real world
Highlights
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Lenvatinib plus pembrolizumab is effective in RCC outside of clinical trials.
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A large subset of patients required treatment adjustments due to AEs.
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Dose adjustments and treatment interruptions do not adversely impact outcomes.
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Proactive monitoring and management of AEs are essential.
Introduction
Immune checkpoint inhibitor (ICI)-based combination therapies, either as double checkpoint inhibition or combined with tyrosine kinase inhibitors (TKIs), are currently standard of care as first-line treatment of patients with advanced renal cell carcinoma (RCC).1, 2, 3 In pivotal trials, the combinations of nivolumab plus ipilimumab, axitinib plus pembrolizumab, cabozantinib plus nivolumab, axitinib plus avelumab and lenvatinib plus pembrolizumab demonstrated significantly superior progression-free survival (PFS) and overall survival (OS)—except for avelumab plus axitinib which demonstrated no significant OS advantage—compared with standard arm sunitinib.4, 5, 6, 7, 8
Lenvatinib is a multiple receptor TKI with antiangiogenic activity. It inhibits vascular endothelial growth factor receptors 1-3, fibroblast growth factor receptors 1-4, c-KIT, RET proto-oncogene and platelet-derived growth factor receptor-α.9,10 Pembrolizumab is a monoclonal antibody against programmed cell death protein 1 (PD-1), which prevents the PD-1 receptor from switching off immune cells and thus increases the immune system’s ability to kill tumor cells.11 Both drugs have shown antitumor activity both as monotherapy and in combination treatment in patients with RCC.12, 13, 14
In the phase III CLEAR trial for patients with clear-cell RCC (ccRCC), the median PFS (mPFS) for lenvatinib plus pembrolizumab was significantly superior with 23.9 months compared with 9.2 months for sunitinib [hazard ratio (HR) 0.39, 95% confidence interval (CI) 0.32-0.49].6 In the phase II KEYNOTE-B61 trial for patients with non-clear cell RCC, the mPFS was 18.0 months and objective response rate (ORR) 49%.15
Adverse events (AEs) led to dose reduction of lenvatinib in 68.8%, interruption of either one or both drugs in 78.4% and discontinuation of either one or both drugs in 37.2% of patients in the CLEAR trial.6 In the KEYNOTE-B61 study, a dose reduction of lenvatinib was described in 34%, an interruption of either one or both drugs in 72% and a discontinuation of either one or both drugs in 20% of patients.15
However, the results of pivotal trials cannot be transferred without restriction to patients in real-world medical care outside of clinical trials due to the strict pre-selection of patients.
Therefore, we investigated the tolerability and effectiveness as well as need for treatment adjustments of lenvatinib plus pembrolizumab in patients with RCC in a real-world population.
Patients and methods
Patients with advanced RCC treated with lenvatinib plus pembrolizumab as standard-of-care first-line therapy at 18 centers in Germany and Austria were included in this analysis. Lenvatinib was administered orally with 20 mg daily as standard dose. Pembrolizumab was administered either with 200 mg every 3 weeks or with 400 mg every 6 weeks intravenously. Treatment was started between October 2020 and December 2023.
Demographic data, comorbidities, initial tumor stage according to TNM (tumor–node–metastasis) classification, histology, sites of metastases at start of treatment, International Metastatic RCC Database Consortium (IMDC) score, treatment adjustments such as dose reduction, interruption and discontinuation, AEs, treatment response and death were recorded. Treatment response was analyzed by local investigators without central review according to RECIST 1.1. Best response and date of progression, if applicable, were documented. AEs were retrospectively assessed based on clinical records according to the Common Terminology Criteria for Adverse Events (CTCAE) v5.0. Data collection was carried out by local physicians using a data template provided in advance.
OS was calculated from the start of treatment until death from any cause, with censoring of patients known to be alive at the time of last follow-up. PFS was calculated from the start of treatment until relapse or death. In patients without recurrence, PFS was censored at the last examination without evidence for a relapse. Both median estimates for OS and PFS were calculated using the Kaplan–Meier method. Median follow-up was estimated based on the time to censoring among those who are censored. In addition, the stability intervals were given for PFS and OS.16 The Cox proportional hazards regression model was used for uni- and multivariate analyses with a combination procedure of forward and backward selection of risk factors based on the Akaike information criterion (AIC; i.e. the procedure searched for the smallest AIC among all possible models).17 A subgroup analysis was conducted specifically for patients with clear-cell histology, evaluating treatment response, PFS and OS. P values <0.05 were defined as significant. Statistical analyses were carried out using IBM SPSS Statistics version 29.0 (IBM Corp., Armonk, NY) and R software package, version 4.4.1 (Foundation for Statistical Computing, Vienna, Austria). This retrospective study was carried out in line with the principles of the Declaration of Helsinki and approved by the Ethics Committee of University Heidelberg (S-510/2022) and institutional review boards of participating centers.
Results
A total of 145 patients were included in this analysis. Detailed patient characteristics are summarized in Table 1. The median age at diagnosis was 63 years (range 21-87 years). The majority of patients were male (69%). The Eastern Cooperative Oncology Group performance status (ECOG PS) was 0, 1, 2 and 3 in 54% (n = 79), 32% (n = 46), 8% (n = 12) and 6% (n = 8) of patients, respectively. The most common predominant histological subtype was ccRCC (88%; n = 128). According to the IMDC risk score, favorable, intermediate and poor risk were reported in 26% (n = 37), 51% (n = 74) and 23% (n = 34) of patients, respectively. Previous nephrectomy or partial nephrectomy was documented for 59% of patients (n = 86). Forty-seven percent of patients (n = 68) would not meet the inclusion or exclusion criteria of the CLEAR trial, mainly due to concomitant diseases (19%), an ECOG PS ≥2 (14%), histological subtype (12%) or central nervous system (CNS) involvement (10%). Supplementary Table S1, available at https://doi.org/10.1016/j.esmorw.2025.100142, provides an overview of the reasons for potential CLEAR ineligibility.
Table 1.
Patient characteristics
| Characteristic | Lenvatinib plus pembrolizumab (n = 145) |
|---|---|
| Age (years) | |
| Median | 63 |
| Range | 21-87 |
| Age <65 years, n (%) | 80 (55) |
| Sex, n (%) | |
| Male | 100 (69) |
| Female | 45 (31) |
| T stage at initial diagnosis, n (%) | |
| T1 | 35 (24) |
| T2 | 18 (12) |
| T3 | 52 (36) |
| T4 | 16 (11) |
| TX | 24 (17) |
| N stage at initial diagnosis, n (%) | |
| N0 | 67 (46) |
| N1 | 36 (25) |
| NX | 42 (29) |
| M stage at initial diagnosis, n (%) | |
| M0 | 78 (54) |
| M1 | 67 (46) |
| ECOG PS, n (%) | |
| 0-1 | 125 (86) |
| ≥2 | 20 (14) |
| IMDC risk group, n (%) | |
| Favorable | 37 (26) |
| Intermediate | 74 (51) |
| Poor | 34 (23) |
| Histological subtype, n (%) | |
| Clear cell | 128 (88) |
| Papillary | 6 (4) |
| Chromophobe | 3 (2) |
| Unclassified (NOS) | 5 (3) |
| Others | 3 (2) |
| Any RCC subtype with sarcomatoid features, n (%) | 5 (3) |
| No. of metastatic organs or sites | |
| Median | 2 |
| Range | 0-8 |
| Organs or sites of metastasis ≥2, n (%) | 103 (71) |
| Site of metastasis, n (%) | |
| Lung | 101 (70) |
| Lymph node | 65 (45) |
| Bone | 47 (32) |
| Liver | 27 (19) |
| Adrenal gland | 26 (18) |
| Soft tissue | 18 (12) |
| Pancreas | 15 (10) |
| Brain | 14 (10) |
| Peritoneum | 10 (7) |
| Others | 14 (11) |
| Previous nephrectomy or partial nephrectomy, n (%) | 86 (59) |
| Previous metastasectomy, n (%) | 34 (23) |
| Previous radiation, n (%) | 17 (12) |
| Adjuvant immunotherapy, n (%) | 4 (3) |
ECOG, Eastern Cooperative Oncology Group; IMDC, International Metastatic RCC Database Consortium; NOS, not otherwise specified; PS, performance status.
Any-grade AEs occurred in 94% of patients, with fatigue (50%; n = 73), hypertension (39%; n = 56) and diarrhea (38%; n = 55) as most common toxicities. Grade ≥3 AEs were reported in 59% of patients. Hypertension (16%; n = 23), diarrhea (10%; n = 14) and infections (10%; n = 14) were identified as most common grade ≥3 AEs. Table 2 provides an overview of AEs. The frequency of AEs stratified by ECOG PS, sex and age is presented in Supplementary Table S2, available at https://doi.org/10.1016/j.esmorw.2025.100142. Diarrhea (P = 0.023) occurred significantly more common in patients with an ECOG PS <2 compared with those with an ECOG PS ≥2, whereas infections (P = 0.008) were significantly more common in patients with an ECOG PS ≥2. Females experienced nausea significantly more frequently than males (P = 0.034). Patients aged ≥70 years suffered significantly more often from fatigue compared with younger patients, whereas rash was significantly more frequent in those aged <70 years.
Table 2.
Adverse events
| Event | Any grade (n = 145) n (%) |
Grade ≥3 (n = 145) n (%) |
|---|---|---|
| Any event | 137 (94) | 85 (59) |
| Fatigue | 73 (50) | 5 (3) |
| Hypertension | 56 (39) | 23 (16) |
| Diarrhea | 55 (38) | 14 (10) |
| Hypothyroidism | 44 (30) | 1 (1) |
| Nausea | 38 (26) | 7 (5) |
| Weight loss | 35 (24) | 4 (3) |
| Rash | 33 (23) | 2 (1) |
| Infections | 27 (19) | 14 (10) |
| Elevated transaminases/hepatitis | 27 (19) | 9 (6) |
| Stomatitis | 23 (16) | 0 |
| Arthralgia | 20 (14) | 1 (1) |
| Decreased appetite | 18 (12) | 4 (3) |
| Dysphagia | 17 (12) | 0 |
| Dysgeusia | 15 (10) | 1 (1) |
| Pneumonitis | 14 (10) | 5 (3) |
| Palmar-plantar erythrodysesthesia syndrome | 14 (10) | 1 (1) |
| Dysphonia | 13 (9) | 1 (1) |
| Others | 53 (37) | 24 (17) |
Interruptions of at least one of the drugs due to toxicities were required in 68% of patients (n = 99). Lenvatinib had to be interrupted in 60% of patients (n = 87), in 27% (n = 39) even several times. The dose of lenvatinib was reduced in 59% of all patients (n = 85). Pembrolizumab had to be interrupted in 35% of patients (n = 51), in 8% (n = 12) several times. Steroids for immune-related AEs (irAEs) were required in 25% of patients (n = 36). Lenvatinib, pembrolizumab or both drugs were permanently discontinued due to toxicities in 18% (n = 26), 16% (n = 23) and 9% (n = 13), respectively.
Treatment response is demonstrated in Table 3. For the entire cohort, the ORR was 66% (n = 95), with 8% of patients (n = 12) achieving a complete remission (CR). The disease control rate (DCR) was 81% (n = 118). Primary progression was seen in 8% of patients (n = 12). Treatment response was unknown or not evaluable in 10% of patients (n = 15). In the ccRCC subgroup, the ORR and DCR were similar to the overall cohort with 66% (CR rate 7%) and 81%, respectively. Details on the best treatment response for the clear-cell subgroup are provided in Supplementary Table S3, available at https://doi.org/10.1016/j.esmorw.2025.100142.
Table 3.
Treatment response according to RECIST 1.1
| n (%) | |
|---|---|
| Objective response rate | 95 (66) |
| Disease control rate | 118 (81) |
| Best overall response | |
| Complete response | 12 (8) |
| Partial response | 83 (57) |
| Stable disease | 23 (16) |
| Progressive disease | 12 (8) |
| Unknown or not evaluable | 15 (10) |
At a median follow-up of 12.2 months (95% CI 10.3-15.5 months) for OS and 12.2 months (95% CI 9.0-16.2 months) for PFS for the entire cohort, 35% of patients (n = 51) experienced disease progression. Twenty-one percent of patients (n = 31) died, most of them due to disease progression. Of the 12 patients with a CR, 11 had an ongoing response at last follow-up.
The mPFS was 20.1 months (95% CI 10.1-24.3 months), and the mOS was not reached. The PFS and OS rates at 6 months were 78% (95% CI 74.7% to 81.9%) and 92% (95% CI 89.6% to 94.2%), and at 12 months 58% (95% CI 52.8% to 62.2%) and 79% (95% CI 75.6% to 83.2%), respectively (Figure 1). Stability intervals for PFS and OS are shown in Supplementary Figure S1, available at https://doi.org/10.1016/j.esmorw.2025.100142. PFS and OS differed significantly between IMDC risk groups. Patients with IMDC favorable risk had a significantly superior PFS (P = 0.02) and OS (P = 0.03) compared with patients with IMDC intermediate or poor risk (Supplementary Figure S2, available at https://doi.org/10.1016/j.esmorw.2025.100142). PFS at 12 months for patients with IMDC favorable, intermediate or poor risk was 75% (95% CI 66.4% to 83.2%), 59% (95% CI 52.2% to 65.0%) and 34% (95% CI 24.6% to 44.0%) and OS at 12 months was 90% (95% CI 84.5% to 95.5%), 79% (95% CI 73.1% to 84.3%) and 70% (95% CI 60.9% to 78.1%), respectively.
Figure 1.
Progression-free survival (PFS) and overall survival (OS). (A) Kaplan–Meier estimates for PFS. (B) Kaplan–Meier estimates for OS. Tick marks indicate censored data. The shaded area indicates the 95% confidence interval (CI).
In the ccRCC subgroup, the mPFS was 22.2 months (95% CI 10.3-24.3 months), while the mOS was not reached (Figure 2). At 6 months, the PFS and OS rates were 77% (95% CI 69% to 84%) and 91% (95% CI 84% to 95%), respectively. At 12 months, the PFS and OS rates were 57% (95% CI 46% to 66%) and 78% (95% CI 69% to 85%), respectively.
Figure 2.
Progression-free survival (PFS) and overall survival (OS) for the clear-cell renal cell carcinoma (RCC) subgroup. (A) Kaplan–Meier estimates for PFS. (B) Kaplan–Meier estimates for OS. Tick marks indicate censored data. The shaded area indicates the 95% confidence interval (CI).
For the entire cohort, treatment adjustments due to AEs did not show any significant disadvantage in outcome. Interruptions or dose reductions of lenvatinib did not show significant differences in PFS (P = 0.13 and P = 0.54, respectively; Figure 3A and E) but were associated with superior OS compared with patients without interruptions or dose reductions (P < 0.001 and P = 0.003, respectively; Figure 3B and F). Interruptions of pembrolizumab or use of steroids due to irAEs did not result in significantly different PFS (P = 0.46 and P = 0.086, respectively; Figure 3C and G) or OS (P = 0.14 and P = 0.94, respectively; Figure 3D and H).
Figure 3.
Progression-free survival (PFS) and overall survival (OS) by treatment adjustments or use of steroids. (A) Kaplan–Meier estimates for PFS by treatment interruption(s) of lenvatinib. (B) Kaplan–Meier estimates for OS by treatment interruption(s) of lenvatinib. (C) Kaplan–Meier estimates for PFS by treatment interruption(s) of pembrolizumab. (D) Kaplan–Meier estimates for OS by treatment interruption(s) of pembrolizumab. (E) Kaplan–Meier estimates for PFS by dose reduction(s) of lenvatinib. (F) Kaplan–Meier estimates for OS by dose reduction(s) of lenvatinib. (G) Kaplan–Meier estimates for PFS by use of steroids. (H) Kaplan–Meier estimates for OS by use of steroids. Tick marks indicate censored data.
In univariate Cox regression, CLEAR eligibility was associated with a significantly lower risk of progression (HR 0.46, 95% CI 0.28-0.76, P = 0.003), whereas ECOG PS ≥2 (HR 4.26, 95% CI 2.35-7.72, P < 0.001), M1 status at diagnosis (HR 1.69, 95% CI 1.02-2.8, P = 0.043), presence of lung metastases (HR 2.03, 95% CI 1.1-3.76, P = 0.024) and IMDC score (HR 1.26, 95% CI 1.07-1.49, P = 0.007) were associated with a significantly higher risk of progression. Furthermore, univariate Cox regression indicated that CLEAR eligibility was associated with a significantly lower risk of death (HR 0.39, 95% CI 0.19-0.82, P = 0.013), whereas ECOG PS ≥2 (HR 6.94, 95% CI 3.36-14.34, P < 0.001), presence of lung metastases (HR 3.58, 95% CI 1.25-10.26, P = 0.017), presence of liver metastases (HR 2.25, 95% CI 1.06-4.78, P = 0.035), number of affected organs (HR 1.26, 95% CI 1.03-1.53, P = 0.026) and IMDC score (HR 1.43, 95% CI 1.14-1.8, P = 0.002) were associated with a significantly higher risk of death. Multivariate analysis identified ECOG PS as an independent prognostic factor for both PFS (HR 3.84, 95% CI 2.09-7.05, P < 0.001) and OS (HR 5.55, 95% CI 2.65-11.63, P < 0.001) as well as sex as an independent prognostic factor for PFS with an advantage for male sex (HR 0.55, 95% CI 0.32-0.93, P = 0.028). The entire model is shown in Supplementary Table S4, available at https://doi.org/10.1016/j.esmorw.2025.100142.
Discussion
ICI-based combination therapies have revolutionized the first-line treatment of patients with advanced RCC.1, 2, 3,18, 19, 20 The results of the pivotal CLEAR study have shown an impressive PFS of 23.9 months for the combination of lenvatinib plus pembrolizumab compared with 9.2 months for standard arm sunitinib.6 However, due to selection bias, the study results cannot be fully extrapolated to patients in routine clinical practice. Thus, real-world data are needed to evaluate the effectiveness and toxicity of this treatment in the real-world population.
Real-world data are increasingly being used and play a crucial role in oncology, providing valuable insights into how well cancer therapies work outside of controlled clinical trials. It helps clinicians make treatment decisions and optimize treatment strategies to better meet the needs of patients.21,22
Hara et al. reported real-world experience in a Japanese cohort of 50 patients with treatment-naive advanced RCC treated with lenvatinib plus pembrolizumab.23 To the best of our knowledge, this is the first European retrospective multicenter study evaluating effectiveness and tolerability as well as the need of treatment adjustments for Caucasian real-world patients with advanced RCC treated with lenvatinib plus pembrolizumab outside of clinical trials. We analyzed a cohort of 145 patients from different centers including both academic and community hospitals. Compared with the patient characteristics of the CLEAR cohort, the median age, sex ratio and localization of metastases were comparable to our cohort. However, our cohort had a higher proportion of patients with poor risk according to IMDC with 23% versus 9.3% in the CLEAR study, 14% of patients with an ECOG PS ≥2 and 12% of patients with a non-clear-cell histology, which were excluded in the CLEAR study. In addition, the rate of nephrectomies or partial nephrectomies was lower in our cohort at 59% versus 74% in the CLEAR study.6
Almost half of the patients (47%) in our cohort would not have met the eligibility criteria of the CLEAR study according to the records, most frequently due to comorbidities, an ECOG PS ≥2, the histological subtype or uncontrolled CNS metastases. This emphasizes that the majority of patients in our clinical routine are not potential trial patients and that there are ultimately no data on treatment efficacy and tolerability for these patients. Thus, it seems worth considering adapting eligibility criteria of future pivotal trials to the actual target population by setting inclusion and exclusion criteria not too strict. This would allow more patients to participate in clinical trials and provide evidence about the efficacy and tolerability of the treatment in the target population.
In our real-world population, the effectiveness of lenvatinib plus pembrolizumab could clearly be confirmed with an ORR of 66% and an mPFS of 20.1 months for the entire cohort. In the ccRCC subgroup, the outcomes were similarly robust, with an ORR of 66% and an mPFS of 22.2 months. As expected, due to the different patient populations, our effectiveness results were slightly lower compared with the CLEAR trial with an ORR of 71% and an mPFS of 23.9 months.6 Besides the differences in the population under study, other factors may contribute to such differences. The absence of a protocol to homogenize treatment and disease management and the less stringent routine imaging application in the clinic may affect efficacy parameters. However, it should also be noted that the ORR in our analysis was assessed by local investigators, which typically results in higher ORR values compared with central radiology reviews, as carried out in the CLEAR trial.
The real-world study by Hara et al., which also included both ccRCC and non-clear-cell RCC patients, reported an ORR of 66%, consistent with our findings. However, with a median follow-up of 11 months, the 1-year PFS rate of 73.5% and 1-year OS rate of 90.0% were higher than our results, which demonstrated a 1-year PFS rate of 58% and a 1-year OS rate of 79%.23
Among others, our univariate analyses showed that CLEAR eligibility was associated with a significantly superior PFS and OS, whereas an ECOG PS ≥2 and a higher IMDC score were associated with a significantly inferior PFS and OS, underlying the difference between our real-world data and those of the CLEAR study. In addition, an ECOG PS ≥2 was identified as an independent prognostic factor for a significantly worse PFS and OS in the multivariate analysis. These results indicate that a decision for therapy initiation in patients with poor ECOG PS should be considered critically and weighed against possible AEs.
Due to the retrospective nature of our analysis, the rate of AEs reported was lower than in the CLEAR study since documentation of AEs in routine clinical practice is less accurate and often limited to those that are classified as relevant by requiring treatment adjustments, requiring therapy themselves or significantly affecting patients’ quality of life. A reporting bias also contributes to the difference between our real-world data and pivotal trial data.
The spectrum of AEs in our cohort was comparable to that of the CLEAR and KEYNOTE-B61 studies. In both our cohort and the CLEAR cohort, the two most common AEs were hypertension and diarrhea.6 Overall, AEs were manageable but required treatment adjustments in a large proportion of patients in our cohort. However, the rate of patients with dose reduction of lenvatinib (59%) or treatment interruptions of at least one of the drugs (68%) was lower than in the CLEAR study (69% and 78%, respectively).6 Based on our broad real-world patient population with more adverse features, we would expect a higher frequency of therapy adaptions to occur. A possible explanation for this observation is probably due to the absence of a detailed protocol that rigidly mandates treatment interruptions and reductions. Although dose reductions or interruptions are common strategies to maximize therapeutic benefit while reducing the risk of toxic effects, a more liberal real-world therapy management was very effective to manage patient’s care and allowed patients to continue life-prolonging therapy over a long period of time. These observations also question whether more liberal therapy management can be applied in clinical trials.
In everyday clinical practice, dose adjustments and treatment interruptions are often accompanied by concerns of insufficient efficacy, both from patients and treating physicians. We were able to demonstrate that such measures had no detrimental influence on effectiveness. It is also known from the CLEAR study that the occurrence of treatment-related AEs is associated with longer treatment duration.6 However, these observations should be interpreted with caution, because immortal time bias applies. Thus, proactive therapy management should be offered early to compensate relevant AEs in order to achieve the longest possible duration of treatment—albeit at a lower dose or with interruptions.
Limitations of our analysis result from the retrospective nature of the analyses, including information bias, and the short median follow-up period of 12.2 months. Additionally, procedures related to dose adjustments, the use of corticosteroids for managing immune-mediated AEs, and follow-up protocols were determined by individual centers based on local standards or treating physicians’ discretion, and not guided by a predefined study protocol.
As several ICI-based combination therapies are currently available for first-line treatment, comparative, ideally prospective studies are needed to investigate the efficacy and toxicity of the approved combination regimens to better understand which patient benefits most from which therapy—such as the CARE1 trial.
Overall, we confirm the effectiveness of lenvatinib plus pembrolizumab for patients with advanced RCC in a real-world cohort with acceptable toxicity. However, AEs should be closely monitored, treated at an early stage and the therapy with lenvatinib plus pembrolizumab should be adjusted if relevant AEs occur.
Acknowledgments
Funding
None declared.
Disclosure
RS has received honoraria from Eisai, Amgen and Pfizer, and has received travel support from Astellas and Ipsen. KS reports personal fees/non-financial support from Astellas, Janssen, Bayer, AstraZeneca, Pfizer, Novartis, EUSApharm, Amgen, Ipsen, Merck, MSD, BMS and Eisai. CD reports personal fees from Ipsen, Janssen-Cilag and Bayer, and travel fees from Bayer, Janssen-Cilag, Ipsen, XEOS medical. SN has received honoraria from Merck, Pfizer, Janssen and travel support from Pfizer. LF reports unpaid relationship to BK Medical. MR has received speaker’s honoraria from Astellas, Merck Healthcare Germany GmbH, Reuter Medico, Bayer; has received consulting fees from Merck Healthcare Germany GmbH, Ipsen, Bayer, Novartis; and has received travel/accommodations/expenses from Ipsen, Merck Healthcare Germany GmbH, Bayer, Roche. FZ reports consulting fees from Apogepha Pharma, Astellas Pharma, AstraZeneca Germany, Bayer Vital, Bristol Myers Squibb, Ipsen, Janssen-Cilag, Merck, MSD, Novartis, Pfizer and Roche; reports payment or honoraria for lectures, presentations or speakers’ bureaus from Amgen, Astellas, Bayer Vital, Ipsen, Janssen-Cilag, Merck, MSD, Pfizer and Sanofi-Aventis; and reports travel support from Astellas, Bayer Vital, Ipsen, Janssen-Cilag and Pfizer. JC reports consulting fees from Janssen-Cilag and travel support from Merck and Pfizer. SV has received speaker’s honoraria from Bristol Myers Squibb, Pfizer, MSD, Merck; has received consultancy fees from MSD, Merck, Janssen; and travel support from Pfizer, Roche, Ipsen. BB has received consulting or advisory fees from BMS, MSD, EISAI, EUSAPharm, Pfizer and has received speaker’s honoraria from Astellas, BMS, MSD, Ipsen, Pfizer. PI has received honoraria from BMS, Bayer, EISAI, EMD-Serono, Ipsen, Merck Serono (Global), Metaplan, MSD, Pfizer, Roche, Apogepha, AstraZeneca, Astella, Deciphera, DKG-Onkoweb, EUSA, FoFM, Id-Institut, MedKom, MTE-Academy, MedWiss, New Concept Oncology, Onkowissen-tv.de, Pharma Mare, ThinkWired!, Schmitz-Communikation, StreamedUP!, Solution Academy, Vivantis, AIO, GSK, Lilly, Niedersächsische Krebsgesellschaft, Novartis, Stiftung Immunonkologie, Wilhelm Sander Stiftung, BB-Biotech, Deutsche Gesellschaft für Thoraxchirurgie. PP has received consulting or advisory fees from AstraZeneca, BMS, Ipsen, Janssen, Merck, MSD, Novartis, Pfizer, Roche; has received honoraria from Apogepha, Astellas, BMS, EISAI, Ipsen, Janssen, Merck, Novartis; and has received travel support from Astellas, Ipsen, Janssen, Medac, Merck, AstraZeneca. MN has received speaker’s honoraria from Janssen-Cilag GmbH and Pfizer Inc. DJ has received consulting fees from Roche Pharma AG, OncoOne Research & Development Research GmbH, Amgen Inc., CureVac AG; has received payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from AstraZeneca GmbH, GRN Klinik Weinheim, BMS GmbH & Co KGaA, MSD, If-Kongress Management GmbH, Gruppe 5 Filmproduktion GmbH, The Norwegian Cancer Society, Dept. of Radiation Medicine, Univ. of Kentucky, Centrum für Integrierte Onkologie Bonn; has received payment for expert testimony: expert opinions for courts, Wilhelm Sander Stiftung; has received support for attending meetings and/or travel: Amgen Inc, Oryx GmbH, Roche Glycart AG, Aex Congresse GmbH, parexel, BMS Stiftung Immunonkologie, BMS GmbH & Co KGaA, Bioevents-congress.com; participation on a data safety monitoring board or advisory board: CureVac AG, Definiens, F. Hoffmann-La Roche Ltd, VAXIMM AG, Oncolytics Biotech Inc, Genmab A-S, Life Science Inkubator GmbH, OncoOne Research & Development Research GmbH; has a leadership or fiduciary role in other board, society, committee or advocacy group paid or unpaid for BMS Stiftung Immunonkologie. VG has stock or other ownership interest from AstraZeneca, Bicycle Therapeutics, Bristol-Myers Squibb, Genmab, MSD; has received honoraria from Advanced Accelerator Applications/Novartis, Amgen, Apogepha, Astellas Pharma, AstraZeneca, Bristol-Myers Squibb, Eisai, Ipsen, Janssen-Cilag, Merck Serono, MSD Oncology, Ono Pharmaceutical, Pfizer; has a consulting or advisory role for Bristol-Myers Squibb, Cureteq, Debiopharm Group, Eisai, Gilead Sciences, Ipsen, Janssen-Cilag, MSD Oncology, Novartis, Oncorena, PCI Biotech, Pfizer, Synthekine; has received research funding (inst) from Amgen, Bicycle Therapeutics, Bristol-Myers Squibb, Gilead Sciences, Ipsen, MSD Oncology, Seagen; and has received travel expenses from AstraZeneca, Ipsen, Janssen, Merck Serono, Pfizer. SZ has received consulting or advisory fees from Amgen, Astellas, AstraZeneca, Bayer, Bristol-Myers Squibb, Eisai, EUSA, Gilead, Ipsen, Janssen, Merck, MSD, Novartis, Pfizer, Roche, Sanofi-Aventis; has received research funding from Eisai; and has received travel/accommodation/expenses from Amgen, Astellas, AstraZeneca, Bayer, Eisai, Ipsen, Janssen, Merck, MSD, Pfizer. All other authors have declared no conflicts of interest.
Data sharing
The data that support the findings of this study are available from the corresponding authors upon reasonable request.
Supplementary data
References
- 1.EAU Guidelines on Renal Cell Carcinoma . EAU Guidelines Office; Arnhem, The Netherlands: 2024. Edn presented at the EAU Annual Congress Paris 2024. [Google Scholar]
- 2.Powles T., Albiges L., Bex A., et al. ESMO Clinical Practice Guideline update on the use of immunotherapy in early stage and advanced renal cell carcinoma. Ann Oncol. 2021;32(12):1511–1519. doi: 10.1016/j.annonc.2021.09.014. [DOI] [PubMed] [Google Scholar]
- 3.Motzer R.J., Jonasch E., Agarwal N., et al. NCCN Guidelines® Insights: Kidney Cancer, Version 2.2024. J Natl Compr Canc Netw. 2024;22(1):4–16. doi: 10.6004/jnccn.2024.0008. [DOI] [PubMed] [Google Scholar]
- 4.Motzer R.J., Tannir N.M., McDermott D.F., et al. Nivolumab plus ipilimumab versus sunitinib in advanced renal-cell carcinoma. N Engl J Med. 2018;378(14):1277–1290. doi: 10.1056/NEJMoa1712126. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Choueiri T.K., Powles T., Burotto M., et al. Nivolumab plus cabozantinib versus sunitinib for advanced renal-cell carcinoma. N Engl J Med. 2021;384(9):829–841. doi: 10.1056/NEJMoa2026982. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Motzer R., Alekseev B., Rha S.Y., et al. Lenvatinib plus pembrolizumab or everolimus for advanced renal cell carcinoma. N Engl J Med. 2021;384(14):1289–1300. doi: 10.1056/NEJMoa2035716. [DOI] [PubMed] [Google Scholar]
- 7.Rini B.I., Plimack E.R., Stus V., et al. Pembrolizumab plus axitinib versus sunitinib for advanced renal-cell carcinoma. N Engl J Med. 2019;380(12):1116–1127. doi: 10.1056/NEJMoa1816714. [DOI] [PubMed] [Google Scholar]
- 8.Motzer R.J., Penkov K., Haanen J., et al. Avelumab plus axitinib versus sunitinib for advanced renal-cell carcinoma. N Engl J Med. 2019;380(12):1103–1115. doi: 10.1056/NEJMoa1816047. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Matsui J., Yamamoto Y., Funahashi Y., et al. E7080, a novel inhibitor that targets multiple kinases, has potent antitumor activities against stem cell factor producing human small cell lung cancer H146, based on angiogenesis inhibition. Int J Cancer. 2008;122(3):664–671. doi: 10.1002/ijc.23131. [DOI] [PubMed] [Google Scholar]
- 10.Yamada K., Yamamoto N., Yamada Y., et al. Phase I dose-escalation study and biomarker analysis of E7080 in patients with advanced solid tumors. Clin Cancer Res. 2011;17(8):2528–2537. doi: 10.1158/1078-0432.CCR-10-2638. [DOI] [PubMed] [Google Scholar]
- 11.Patnaik A., Kang S.P., Rasco D., et al. Phase I study of pembrolizumab (MK-3475; anti-PD-1 monoclonal antibody) in patients with advanced solid tumors. Clin Cancer Res. 2015;21(19):4286–4293. doi: 10.1158/1078-0432.CCR-14-2607. [DOI] [PubMed] [Google Scholar]
- 12.Motzer R.J., Hutson T.E., Glen H., et al. Lenvatinib, everolimus, and the combination in patients with metastatic renal cell carcinoma: a randomised, phase 2, open-label, multicentre trial. Lancet Oncol. 2015;16(15):1473–1482. doi: 10.1016/S1470-2045(15)00290-9. [DOI] [PubMed] [Google Scholar]
- 13.McDermott D.F., Lee J.L., Bjarnason G.A., et al. Open-label, single-arm phase II study of pembrolizumab monotherapy as first-line therapy in patients with advanced clear cell renal cell carcinoma. J Clin Oncol. 2021;39(9):1020–1028. doi: 10.1200/JCO.20.02363. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Taylor M.H., Lee C.H., Makker V., et al. Phase IB/II trial of lenvatinib plus pembrolizumab in patients with advanced renal cell carcinoma, endometrial cancer, and other selected advanced solid tumors. J Clin Oncol. 2020;38(11):1154–1163. doi: 10.1200/JCO.19.01598. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Albiges L., Gurney H., Atduev V., et al. Pembrolizumab plus lenvatinib as first-line therapy for advanced non-clear-cell renal cell carcinoma (KEYNOTE-B61): a single-arm, multicentre, phase 2 trial. Lancet Oncol. 2023;24(8):881–891. doi: 10.1016/S1470-2045(23)00276-0. [DOI] [PubMed] [Google Scholar]
- 16.Erdmann S., Betensky R. KMstability: R tools to report the stability and precision of Kaplan – Meier estimates as well as measures of follow-up in time-to-event studies. SoftwareX. 2024;26 [Google Scholar]
- 17.Gabel M., Hohl T., Imle A., Fackler O.T., Graw F. FAMoS: a Flexible and dynamic Algorithm for Model Selection to analyse complex systems dynamics. PLoS Comput Biol. 2019;15(8) doi: 10.1371/journal.pcbi.1007230. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Bosma N.A., Warkentin M.T., Gan C.L., et al. Efficacy and safety of first-line systemic therapy for metastatic renal cell carcinoma: a systematic review and network meta-analysis. Eur Urol Open Sci. 2022;37:14–26. doi: 10.1016/j.euros.2021.12.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Quhal F., Mori K., Bruchbacher A., et al. First-line Immunotherapy-based combinations for metastatic renal cell carcinoma: a systematic review and network meta-analysis. Eur Urol Oncol. 2021;4(5):755–765. doi: 10.1016/j.euo.2021.03.001. [DOI] [PubMed] [Google Scholar]
- 20.Rassy E., Flippot R., Albiges L. Tyrosine kinase inhibitors and immunotherapy combinations in renal cell carcinoma. Ther Adv Med Oncol. 2020;12 doi: 10.1177/1758835920907504. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Saesen R., Lacombe D., Huys I. Real-world data in oncology: a questionnaire-based analysis of the academic research landscape examining the policies and experiences of the cancer cooperative groups. ESMO Open. 2023;8(2) doi: 10.1016/j.esmoop.2023.100878. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Di Maio M., Perrone F., Conte P. Real-world evidence in oncology: opportunities and limitations. Oncologist. 2020;25(5):e746–e752. doi: 10.1634/theoncologist.2019-0647. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Hara T., Suzuki K., Okamura Y., et al. Efficacy and safety of lenvatinib and pembrolizumab as first-line treatment for advanced renal cell carcinoma patients: real-world experience in Japan. Int J Clin Oncol. 2024;29(12):1931–1936. doi: 10.1007/s10147-024-02633-w. [DOI] [PubMed] [Google Scholar]
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