Literature DB >> 30333065

Patterns, predictors and subsequent outcomes of disease progression in metastatic renal cell carcinoma patients treated with nivolumab.

Haris Zahoor1, Pedro C Barata1, Xuefei Jia2, Allison Martin1, Kimberly D Allman1, Laura S Wood1, Timothy D Gilligan1, Petros Grivas1, Moshe C Ornstein1, Jorge A Garcia1, Brian I Rini3,4.   

Abstract

BACKGROUND: Nivolumab is approved for the treatment of refractory metastatic renal cell carcinoma. Patterns and predictors of progressive disease (PD) on nivolumab, and outcomes in such patients are lacking.
METHODS: A retrospective analysis of patients (pts) with metastatic clear cell renal cell carcinoma (ccRCC) who received nivolumab at Cleveland Clinic (2015-2017) was performed. PD was defined per Response Evaluation Criteria in Solid Tumors (RECIST) v1.1 or clinical progression as per treating physician. Univariate analyses (UVA) and multivariate analyses (MVA) were used to identify clinical and laboratory markers as potential predictors of progression-free survival (PFS).
RESULTS: Ninety patients with mean age of 65, 74% men, and 83% good or intermediate International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) risk group were included. Median number of prior systemic treatments was 2 (range, 1-6). Median overall survival (OS) and PFS were 15.8 and 4.4 months, respectively. Fifty-seven patients (63%) had PD and 44% of patients with radiographic PD had new organ sites of metastases with brain (8/23, 35%) being the most common. Twelve patients received treatment beyond progression (TBP), and among 6 patients with available data, 3 (50%) had any tumor shrinkage (2 pts. with 17% shrinkage, one pt. with 29% shrinkage). Of 57 patients with PD, 28 patients (49%) were able to initiate subsequent treatment, mainly with axitinib and cabozantinib, while 40% of patients were transitioned to hospice after PD. In MVA, a higher baseline Neutrophil-to-Lymphocyte ratio (NLR) (HR, 1.86; 95% CI, 1.05-3.29; p = 0.033) was associated with an increased risk of progression, whereas higher (> 0.1 k/uL) baseline eosinophil count was associated with a lower risk of progression (HR, 0.54; 95% CI, 0.30-0.98; p = 0.042).
CONCLUSION: Brain was the most common site of PD in patients treated with nivolumab, and only half of patients progressing on nivolumab were able to initiate subsequent treatment. The risk of PD increased with a higher baseline NLR and reduced with a higher baseline eosinophil count.

Entities:  

Keywords:  Biomarker; Clear cell; Failure; Immunotherapy; Nivolumab; Renal cell carcinoma

Mesh:

Substances:

Year:  2018        PMID: 30333065      PMCID: PMC6192175          DOI: 10.1186/s40425-018-0425-8

Source DB:  PubMed          Journal:  J Immunother Cancer        ISSN: 2051-1426            Impact factor:   13.751


Background

The treatment of advanced clear cell renal cell carcinoma (ccRCC) has dramatically changed over the last decade with introduction of targeted agents including tyrosine kinase inhibitors (TKI) [1]. Although these agents have significantly improved outcomes, they rarely result in complete responses [2, 3]. Renal cell carcinoma has been considered an immune-responsive tumor and immunotherapy with high dose IL-2 has been used in select patients leading to complete and durable responses in a subset of patients [4]. More refined and novel immunotherapies have been developed due to improved understanding of T cell function and associated immunosuppressive molecules such as cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), program death 1 (PD-1) and PD-1 ligand 1 (PD-L1), called immune checkpoints [5]. Nivolumab, a fully human IgG4 anti-PD- antibody, is the first approved checkpoint inhibitor for the treatment of metastatic RCC refractory to antiangiogenic therapy based on a phase III clinical trial [6]. As compared to everolimus, a mammalian target of rapamycin (mTOR) inhibitor, nivolumab improved overall survival (OS) (HR: 0.73 p = 0.002). The overall response rate with nivolumab was 25% vs. 5% with everolimus (p < 0.001). The treatment was well tolerated with 19% treatment related grade 3 or 4 Adverse Events (AEs) in nivolumab vs. 37% in everolimus patients. Based on these data, nivolumab became the preferred standard of care treatment for metastatic RCC patients who have progressed on previous antiangiogenic therapy. Although nivolumab has prompted a paradigm shift in the treatment of metastatic RCC, only a subset of patients benefit from this treatment, and hence identifying predictive biomarkers is an area of active research. The CheckMate 025 trial investigated the role of PD-L1 expression as a marker of response [6]. Patients with higher PD-L1 expression were shown to have worse outcomes as compared to those with low PD-L1 expression. However, both groups appeared to derive the same benefit from nivolumab relative to everolimus, indicating that PD-L1 expression was prognostic but not predictive and thus cannot be used to select patients for treatment. Similarly, little is known about the patterns of disease progression and outcomes of patients who progress on nivolumab treatment. The main objective of this analysis was to evaluate patterns and predictors of failure, and subsequent outcomes in patients treated with nivolumab. These data can generate hypotheses regarding markers of response to select appropriate patients for treatment, and also provide prognostic information to patients and physicians.

Methods

After obtaining approval from Institutional Review Board of Cleveland Clinic, we performed a retrospective review of patients with advanced ccRCC who received nivolumab at Cleveland Clinic (2015–2017). Data on patient characteristics, treatment patterns and clinical follow up was extracted from chart review. Baseline laboratory parameters at the time of treatment of initiation, including Neutrophil-to-Lymphocyte ratio (NLR), absolute eosinophil count, absolute monocyte count and absolute basophil count, were also extracted from chart review. Patients were divided into two groups at a three-month landmark. The first group, called the PD group, was comprised of patients with progressive disease as their final outcome at the time of analysis. The second group, called NPD, was comprised of patients who had not progressed on nivolumab at time of analysis. PD was defined per Response Evaluation Criteria in Solid Tumors (RECIST) v1.1 or clinical PD defined as lack of clinical benefit from nivolumab as per treating physician discretion. The interval of radiographic response evaluation was not predefined although generally done every 12 weeks and baseline neuroimaging was not routinely done.

Statistical analyses

Categorical clinic-pathologic factors were summarized. A landmark analysis at 3 months was performed to explore any potential differences in baseline characteristics between PD and NPD groups. Fisher’s exact text and the Wilcoxon rank sum test were used to compare clinic-pathologic factors between two groups. OS and PFS were summarized using the Kaplan-Meier method. PFS was defined as the time from the first dose of nivolumab to radiographic or clinical progression or death, whichever came first, censored at last follow-up for patients who had not progressed. OS was calculated as the time from the first dose of nivolumab to the date of death or last follow-up. Cox proportional hazards models were used for comparisons between factors. A p value ≤0.05 was regarded as significant. Univariate analyses (UVA) were used for clinic-pathologic factors and baseline patient characteristics. The multivariable analysis (MVA) was performed by using the step-wise variable selection with IMDC and adjusted for number of prior treatment and prior treatment with IL-2 or interferon (IFN) (Additional file 1), and was used to identify potential predictors of progression-free survival (PFS). Recursive partitioning method was used to identify cut-off values for NLR and eosinophil counts. All data analyses were carried out using R software (3.5.0).

Results

Baseline patient characteristics

Ninety patients with mean age of 65 (SD, 9.88) were included in the analysis. Of these, 74% were men and 82% had Eastern Cooperative Oncology Group (ECOG) Performance Status of 1–2. Eighty-three percent of patients had a good or intermediate International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) risk category [7]. The median number of prior systemic treatments was 2 (range, 1–6). Prior nephrectomy was done in 97% of patients. Sunitinib (71%) was the most common prior treatment used. (Table 1).
Table 1

Baseline Patient Characteristics

CharacteristicsNo (%)n = 90
Mean age, years (SD)65 (9.88)
Male Gender67 (74)
ECOG PS
 034 (41)
 133 (40)
  > 215 (18)
IMDC Risk Group
 Favorable12 (14)
 Intermediate61 (69)
 Poor15 (17)
 Prior Nephrectomy67 (97)
 No of prior systemic therapies, median, No. (range)2 (1, 6)
No of prior systemic therapies
 142 (47)
 224 (27)
 316 (18)
 46 (7)
  > 52 (2)
Most common prior systemic therapies
 Sunitinib64 (71)
 Pazopanib30 (33)
 Axitinib35 (39)
Sites of metastases at baseline
 Brain14 (16)
 Bones37 (41)
 Lungs65 (72)
 Liver27 (30)
 Lymph Nodes58 (64)
 Pleural18 (20)
 Adrenal20 (22)
Baseline Patient Characteristics The baseline characteristics of patients in the PD and NPD groups at 3 months after initiating nivolumab were similar except higher incidence of baseline lung (85% vs. 63%, p = 0.046), lymph node (79% vs. 53%, p = 0.019) and pleural metastases (33% vs. 10%, p = 0.016) in PD group. (Table 2).
Table 2

Comparison of PD and NPD using landmark analysis at 3 months

CharacteristicsPD Group N (%)n = 49NPD Group N (%)n = 39p-value
Mean age, years (SD)66 (10.20)64 (9.61)0.401
Male Gender33 (67)33 (85)0.107
ECOG PS0.106
 023 (52)10 (27)
 115 (34)18 (49)
  > 26 (14)9 (24)
IMDC Risk Group0.139
 Favorable8 (17)4 (10)
 Intermediate35 (73)24 (63)
 Poor5 (10)10 (26)
Prior Nephrectomy35 (97)30 (97)1.000
No of prior systemic therapies, median, No. (range)
No of prior systemic therapies0.404
 125 (51)15 (38)
 210 (20)14 (36)
 310 (20)6 (15)
  > 43 (6)4 (10)
Common prior systemic therapies
 Sunitinib38 (78)24(61)0.161
 Pazopanib15 (31)15 (38)0.586
 Axitinib18 (37)17 (44)0.665
Sites of metastases at baseline
 Brain7 (18)7 (14)0.862
 Bones13 (33)24 (49)0.208
 Lungs33 (85)31 (63)0.046
 Liver14 (36)12 (24)0.352
 Lymph Nodes31 (79)26 (53)0.019
 Pleural13 (33)5 (10)0.016
 Adrenal9 (23)11 (22)1.000

Two patients were excluded from this analysis because of lack data regarding their PD status

Comparison of PD and NPD using landmark analysis at 3 months Two patients were excluded from this analysis because of lack data regarding their PD status Common sites of metastases at baseline included lung (72%), lymph nodes (64%) and bone (41%). Brain metastases were present in 14 (16%) patients. All patients had received central nervous system (CNS)-directed therapy (Whole brain radiation treatment; 2 patients, Gamma Knife surgery; 10 patients, and surgical resection plus Gamma Knife surgery; 2 patients). Of these 14 patients, further progression of brain metastases was observed in 3 (21%) patients while receiving nivolumab. Two out of these 3 patients were treated with nivolumab beyond progression along with palliative radiation therapy. Two out of 14 patients had overall clinical deterioration, not attributed to nivolumab, and died. The remaining 9 patients had no further evidence of progression of brain metastases on nivolumab treatment.

Efficacy summary

With the median follow up of 7.6 months after initiation of nivolumab, patients remained on treatment for a median of 2.8 months. Among 79 patients evaluable for response, the overall response rate was 15% (one patient with complete response), 38% had stable disease and 47% had progressive disease as the best objective response to nivolumab. The additional 11 patients were either lost to follow up or had missing data to assess response. (Fig. 1).
Fig. 1

Swimmer plot of time on treatment for evaluable patients (n = 79)

Swimmer plot of time on treatment for evaluable patients (n = 79) The median time to response was 2.4 months. The estimated median PFS and OS were 4.8 and 15.8 months, respectively. The median PFS of patients with one prior therapy was 5 months as compared to 2.9 months in patients with more than one prior therapy (p = 0.54).

Patterns of disease progression

Overall 57 patients (63%) developed PD. Among these patients, 51 (89%) had radiographic PD as per RECIST, 5 patients (9%) had evidence of clinical PD and one patient had both clinical and radiographic PD. Among patients who developed radiographic PD, 23 patients (44%) had new organ sites of metastases. The most common sites of new metastases at time PD were brain (35%) followed by liver (17%), soft tissue (17%) and loco-regional (17%). (Table 3).
Table 3

Patterns of disease progression and subsequent outcomes

Characteristicsn = 90
PD57 (63)
 RECIST51 (89)
 Clinical5 (9)
 Both1 (2)
Patients with new organ sites at time of RECIST PD23 (44)
New organ sites at time of RECIST PD
 Brain8 (35)
 Bones1 (4)
 Liver4 (17)
 Soft tissue4 (17)
 Pleural1 (4)
 Local4 (17)
 Adrenal3 (13)
Management after PD
 Subsequent systemic treatment28 (49)
 Hospice23 (40)
 Died3 (5)
Subsequent therapies in PD group after nivolumab discontinued
 Cabozantinib6 (21)
 Axitinib14 (50)
 Everolimus1 (4)
 Temsirolimus3 (11)
 Sunitinib2 (7)
 Others*2 (7)

*One patient was enrolled in a clinical trial investigating an experimental drug in combination with Atezolizumab. A second patient was enrolled in a clinical trial and randomized to receive tivozanib

Patterns of disease progression and subsequent outcomes *One patient was enrolled in a clinical trial investigating an experimental drug in combination with Atezolizumab. A second patient was enrolled in a clinical trial and randomized to receive tivozanib CNS directed local therapy was offered to all patients (3 out of 8 patients) who developed brain metastases and continued nivolumab treatment (beyond progression) in this study.

Treatment beyond progression

Twelve patients (21%) received treatment beyond progression (TBP) with a median duration of TBP of 2.8 months (95% CI, 0.6–5.0). However, only 6 patients had follow up data available to evaluate outcomes of TBP. Among these 6 patients with available data, 3 (50%) had any tumor shrinkage. Two patients had a 17% reduction in tumor burden whereas one patient had a 29% reduction in tumor burden.

Outcomes after disease progression

Of 57 patients with PD, 50% were able to initiate subsequent systemic treatment. Axitinib (50%) and cabozantinib (21%) were the most common subsequent treatments. Forty percent of patients were transitioned to hospice and were not able to receive any subsequent systemic treatment after progression on nivolumab. Patients who were unable to initiate subsequent treatment after progression on nivolumab appeared to be frail (ECOG PS > 2; 27% vs. 14%, p = 0.57) and poorer risk (IMDC poor risk 29% vs. 10%, p = 0.14) as compared to patients who initiated subsequent systemic treatment.

Univariate and multivariate analyses

In univariate analysis, variables associated with poor PFS included Karnofsky performance status < 80% (HR 1.86; 95% CI, 1.03–3.35; p = 0.039), presence of lung metastases (HR 1.89; 95% CI, 1.04–3.41; p = 0.035), presence of lymph node metastases (HR 1.75; 95% CI, 1.04–2.95; p = 0.036), and presence of pleural metastases (HR 2.64; 95% CI, 1.47–4.74; p = 0.001). Baseline NLR (HR 1.03; 95% CI, 1.00–1.07; p = 0.05) and eosinophil count (HR 1.01; 95% CI,1.00–1.02; p = 0.016) were both inconclusive in univariate analysis. In MVA, higher (> 4.2) baseline NLR (HR, 1.86; 95% CI, 1.05–3.29; p = 0.033) was associated with an increased risk of progression, whereas higher (> 0.1 k/uL) baseline eosinophil count was associated with lower risk of progression (HR, 0.54; 95% CI, 0.30–0.98; p = 0.042). Presence of baseline lung, lymph node and pleural metastases were associated with higher risk of progression in multivariate model but did not reach statistical significance. (Table 4).
Table 4

Multivariable analysis of PFS

ParameterHazard Ratio95% Confidence Intervalp-value
Baseline Lung Metastases1.920.96, 3.860.066
Baseline LN Metastases1.670.88, 3.190.12
Baseline Pleural Metastases1.690.86, 3.330.1
IMDC Intermediate Risk Group (Favorable as reference)0.620.25, 1.560.31
IMDC Poor Risk Group (Favorable as reference)0.510.16, 1.660.26
Baseline Neutrophil to Lymphocyte Ratio (NLR) < 4.2 vs > = 4.21.861.05, 3.290.033
Baseline Absolute Eosinophil Count (k/uL) < 0.1 vs > = 0.10.540.30, 0.980.042
Multivariable analysis of PFS

Discussion

Immune checkpoint inhibitors (ICI) have prompted a paradigm shift in many cancers including RCC [5]. Nivolumab has shown promising activity and an overall survival advantage with an excellent safety profile in refractory metastatic RCC patients. ICI are now being investigated in the first line setting either alone, or in combination with another ICI or a VEGF-directed agent. Combination treatment with nivolumab and ipilimumab, an anti-CTLA 4 antibody, was recently approved by FDA for intermediate or poor-risk RCC patients based on Checkmate 214 trial [8]. This study demonstrated a robust clinical activity of this combination, and patients had a significant lower risk of death when compared to sunitinib. Of note, in an exploratory analysis of this study involving favorable risk patients, sunitinib had improved ORR and PFS when compared to nivolumab plus ipilimumab. Similarly, a randomized phase III trial met its primary endpoint demonstrating superiority of combination of atezolizumab, an anti-PD-L1 antibody, in combination with bevacizumab, as compared to sunitinib [9]. Pembrolizumab monotherapy in treatment naïve patients has also shown promising clinical activity in a phase II trial [10]. These data suggest that ICI, either in combination with another ICI or VEGF directed agent, or monotherapy, will become standard of care for treatment naïve RCC patients in near future. Therefore, outcomes of these patients after treatment failure will be instructive to improve therapeutic options in the refractory space, and also provide prognostic information to patients and clinicians. The present retrospective analysis demonstrated broadly similar efficacy for nivolumab monotherapy in refractory RCC as noted in the registration trial. For example, the median PFS was 4.8 months in the current analysis as compared to 4.6 months. The ORR (15% vs. 25%) and median OS (15.8 vs. 25 months) were lower than the registration trial. However, it should be noted that patients included in this analysis were more heavily pretreated when compared to the registration trial of nivolumab. Similarly, there were fewer favorable risk patients included in the current study (13% favorable IMDC risk group) as compared to the registration trial. Notably, however, a higher incidence of new brain metastases at time of PD was observed and only a subset of patients were able to initiate subsequent systemic therapy after PD. The incidence of brain metastases in the current analysis is higher than what has been reported in RCC patients in the literature either on observation or active treatment [11]. Several hypothesis-generating explanations may explain this observation including poor permeability of the blood-brain barrier [12]. It is also plausible that higher incidence of brain metastases in current study is a reflection of natural history of disease and these events were captured more often due to a heavily pretreated and refractory patient population. Since patients with active or untreated brain metastases are often excluded from phase III clinical trials [13], level I evidence regarding the safety and efficacy of ICI in brain metastases, specifically symptomatic brain metastases, is lacking. Retrospective data suggests that metastatic RCC patients with brain metastases don’t derive benefit from nivolumab and local CNS therapy should be incorporated in the treatment plan [14]. Comparison of patients with limited benefit from ICI to those who derive more durable and substantial benefit can identify potential clinical variables, which can be used to select patients to maximize clinical benefit and avoid unnecessary toxicities. In this study, a landmark analysis at 3 months after initiating nivolumab was therefore performed to divide patients into PD and NPD groups. These two groups were then compared and showed no major differences in clinical variables. Previous studies in RCC have shown that clinical characteristics do not predict response to immunotherapy except poor IMDC risk score, which is associated with an enhanced response to treatment. Several molecular and genetic predictive biomarkers of immunotherapy are under investigation including PD-L1 expression [15], tumor mutational burden [16], gene expression signatures [17] and tumor infiltrating lymphocytes [18]. However, reproducibility, pathologic specimen requirement, tumor heterogeneity and sampling variability, have been major challenges in the development and clinical utilization of these biomarkers [19]. Serum markers such as peripheral blood cell counts are readily available, and may predict response to immunotherapy. A higher baseline or increased absolute lymphocyte count with treatment is associated with improved response to immunotherapy and overall survival in some series [20, 21]. This association may be due to the fact that immune checkpoints are expressed on various lymphocyte populations and hence a higher lymphocyte peripheral blood count may be associated with more PD-L1 positive lymphocytes in the tumor and thus greater anti-tumor effects with immunotherapy [22, 23]. An elevated peripheral neutrophil count, on the other hand, is a marker of chronic inflammation leading to impaired immunity [24], tumor growth, metastases and poor outcomes in cancer patients [25]. In vitro studies have shown neutrophils can suppress the cytotoxic activity of lymphocytes when they are co-cultured, and this suppression is dose-dependent [26]. NLR, derived from the quotient of the absolute neutrophil count and the absolute lymphocyte count, is essentially a reflection of hemostasis between cancer inflammation and host anti-tumor response [27]. A higher NLR has been shown to be prognostic in multiple solid tumors with varying thresholds of being used to define a higher or a significant value [28]. Specifically in RCC, Templeton et al. demonstrated that RCC patients receiving targeted therapy have worse outcome with higher baseline and on-treatment increase in NLR [29]. NLR has also shown similar prognostic value in RCC patients treated with ICI [30]. An increased eosinophil count can be seen from an immuno-allergic process or lymphocytosis. Immune checkpoint inhibition can potentially lead to exacerbated allergic manifestations and animal data suggest that CTLA-4 blockade can promote allergic eosinophilic inflammation and antigen-specific IgE secretion [31, 32]. A higher baseline absolute eosinophil count or an increase in eosinophil count with treatment has been shown to correlate with improved OS in melanoma patients treated with immunotherapy [20, 21, 33]. A higher baseline eosinophil count in the current study was associated with favorable outcome, which is consistent with prior studies [20]. This study has several limitations including the selection bias of a retrospective study. Secondly, the study only included patients with clear cell histology, which limits the generalization of these findings to non-clear cell histology. Lack of independent imaging review and inconsistent intervals of response evaluation are also limitations. Clinical PD was not predefined and was based on treating physician discretion. The predictive versus prognostic value of laboratory markers evaluated in this study cannot be determined due to lack of a control arm. In addition, PFS was the clinical readout for the multivariate analysis. PFS may not be the best marker of response to immunotherapy but given lack of complete responses and variable overall survival in this heterogeneous population, it was deemed acceptable to generate a hypothesis of factors affecting outcome to nivolumab in this setting. Lastly, these patients were treated at a tertiary care academic center, which can lead to selection bias.

Conclusions

In conclusion, this study highlights the patterns of disease progression and outcomes after disease progression in metastatic RCC patients treated with nivolumab outside of clinical trial. Further validation in larger cohorts and prospective studies is needed and may help appropriate patient selection to maximize treatment benefit and minimize toxicities. Table S1: Multivariate analysis of PFS after controlling for number of prior treatments. Table S2: Multivariate analysis of PFS after controlling for prior treatment with IL-2 or Interferon (DOCX 15 kb)
  30 in total

1.  Blockade of CTLA-4 promotes airway inflammation in naive mice exposed to aerosolized allergen but fails to prevent inhalation tolerance.

Authors:  L Alenmyr; V Matheu; L Uller; L Greiff; M Malm-Erjefält; H-G Ljunggren; C G A Persson; M Korsgren
Journal:  Scand J Immunol       Date:  2005-11       Impact factor: 3.487

2.  Change in Neutrophil-to-lymphocyte Ratio in Response to Targeted Therapy for Metastatic Renal Cell Carcinoma as a Prognosticator and Biomarker of Efficacy.

Authors:  Arnoud J Templeton; Jennifer J Knox; Xun Lin; Ronit Simantov; Wanling Xie; Nicola Lawrence; Reuben Broom; André P Fay; Brian Rini; Frede Donskov; Georg A Bjarnason; Martin Smoragiewicz; Christian Kollmannsberger; Ravindran Kanesvaran; Nimira Alimohamed; Thomas Hermanns; J Connor Wells; Eitan Amir; Toni K Choueiri; Daniel Y C Heng
Journal:  Eur Urol       Date:  2016-02-28       Impact factor: 20.096

3.  Baseline Peripheral Blood Biomarkers Associated with Clinical Outcome of Advanced Melanoma Patients Treated with Ipilimumab.

Authors:  Alexander Martens; Kilian Wistuba-Hamprecht; Marnix Geukes Foppen; Jianda Yuan; Michael A Postow; Phillip Wong; Emanuela Romano; Amir Khammari; Brigitte Dreno; Mariaelena Capone; Paolo A Ascierto; Anna Maria Di Giacomo; Michele Maio; Bastian Schilling; Antje Sucker; Dirk Schadendorf; Jessica C Hassel; Thomas K Eigentler; Peter Martus; Jedd D Wolchok; Christian Blank; Graham Pawelec; Claus Garbe; Benjamin Weide
Journal:  Clin Cancer Res       Date:  2016-01-19       Impact factor: 12.531

Review 4.  Molecular and Biochemical Aspects of the PD-1 Checkpoint Pathway.

Authors:  Vassiliki A Boussiotis
Journal:  N Engl J Med       Date:  2016-11-03       Impact factor: 91.245

5.  Safety, activity, and immune correlates of anti-PD-1 antibody in cancer.

Authors:  Suzanne L Topalian; F Stephen Hodi; Julie R Brahmer; Scott N Gettinger; David C Smith; David F McDermott; John D Powderly; Richard D Carvajal; Jeffrey A Sosman; Michael B Atkins; Philip D Leming; David R Spigel; Scott J Antonia; Leora Horn; Charles G Drake; Drew M Pardoll; Lieping Chen; William H Sharfman; Robert A Anders; Janis M Taube; Tracee L McMiller; Haiying Xu; Alan J Korman; Maria Jure-Kunkel; Shruti Agrawal; Daniel McDonald; Georgia D Kollia; Ashok Gupta; Jon M Wigginton; Mario Sznol
Journal:  N Engl J Med       Date:  2012-06-02       Impact factor: 91.245

6.  Prognostic factors for overall survival in patients with metastatic renal cell carcinoma treated with vascular endothelial growth factor-targeted agents: results from a large, multicenter study.

Authors:  Daniel Y C Heng; Wanling Xie; Meredith M Regan; Mark A Warren; Ali Reza Golshayan; Chakshu Sahi; Bernhard J Eigl; J Dean Ruether; Tina Cheng; Scott North; Peter Venner; Jennifer J Knox; Kim N Chi; Christian Kollmannsberger; David F McDermott; William K Oh; Michael B Atkins; Ronald M Bukowski; Brian I Rini; Toni K Choueiri
Journal:  J Clin Oncol       Date:  2009-10-13       Impact factor: 44.544

Review 7.  Chemotherapy delivery issues in central nervous system malignancy: a reality check.

Authors:  Leslie L Muldoon; Carole Soussain; Kristoph Jahnke; Conrad Johanson; Tali Siegal; Quentin R Smith; Walter A Hall; Kullervo Hynynen; Peter D Senter; David M Peereboom; Edward A Neuwelt
Journal:  J Clin Oncol       Date:  2007-06-01       Impact factor: 44.544

8.  PD-1 blockade induces responses by inhibiting adaptive immune resistance.

Authors:  Paul C Tumeh; Christina L Harview; Jennifer H Yearley; I Peter Shintaku; Emma J M Taylor; Lidia Robert; Bartosz Chmielowski; Marko Spasic; Gina Henry; Voicu Ciobanu; Alisha N West; Manuel Carmona; Christine Kivork; Elizabeth Seja; Grace Cherry; Antonio J Gutierrez; Tristan R Grogan; Christine Mateus; Gorana Tomasic; John A Glaspy; Ryan O Emerson; Harlan Robins; Robert H Pierce; David A Elashoff; Caroline Robert; Antoni Ribas
Journal:  Nature       Date:  2014-11-27       Impact factor: 49.962

9.  Change in Neutrophil-to-lymphocyte ratio (NLR) in response to immune checkpoint blockade for metastatic renal cell carcinoma.

Authors:  Aly-Khan A Lalani; Wanling Xie; Dylan J Martini; John A Steinharter; Craig K Norton; Katherine M Krajewski; Audrey Duquette; Dominick Bossé; Joaquim Bellmunt; Eliezer M Van Allen; Bradley A McGregor; Chad J Creighton; Lauren C Harshman; Toni K Choueiri
Journal:  J Immunother Cancer       Date:  2018-01-22       Impact factor: 13.751

10.  Significance of baseline and change in neutrophil-to-lymphocyte ratio in predicting prognosis: a retrospective analysis in advanced pancreatic ductal adenocarcinoma.

Authors:  Yang Chen; Huan Yan; YanRong Wang; Yan Shi; GuangHai Dai
Journal:  Sci Rep       Date:  2017-04-09       Impact factor: 4.379

View more
  20 in total

1.  Nivolumab plus ipilimumab versus sunitinib in first-line treatment for advanced renal cell carcinoma: extended follow-up of efficacy and safety results from a randomised, controlled, phase 3 trial.

Authors:  Robert J Motzer; Brian I Rini; David F McDermott; Osvaldo Arén Frontera; Hans J Hammers; Michael A Carducci; Pamela Salman; Bernard Escudier; Benoit Beuselinck; Asim Amin; Camillo Porta; Saby George; Victoria Neiman; Sergio Bracarda; Scott S Tykodi; Philippe Barthélémy; Raya Leibowitz-Amit; Elizabeth R Plimack; Sjoukje F Oosting; Bruce Redman; Bohuslav Melichar; Thomas Powles; Paul Nathan; Stéphane Oudard; David Pook; Toni K Choueiri; Frede Donskov; Marc-Oliver Grimm; Howard Gurney; Daniel Y C Heng; Christian K Kollmannsberger; Michael R Harrison; Yoshihiko Tomita; Ignacio Duran; Viktor Grünwald; M Brent McHenry; Sabeen Mekan; Nizar M Tannir
Journal:  Lancet Oncol       Date:  2019-08-16       Impact factor: 41.316

2.  Prognostic Markers for Refined Stratification of IMDC Intermediate-Risk Metastatic Clear Cell Renal Cell Carcinoma Treated with First-Line Tyrosine Kinase Inhibitor Therapy.

Authors:  Toshio Takagi; Hironori Fukuda; Tsunenori Kondo; Hiroki Ishihara; Kazuhiko Yoshida; Hirohito Kobayashi; Junpei Iizuka; Masayoshi Okumi; Hideki Ishida; Kazunari Tanabe
Journal:  Target Oncol       Date:  2019-04       Impact factor: 4.493

3.  Unique behavior of brain metastases during the treatment of nivolumab for metastatic renal cell carcinoma.

Authors:  Tsunenori Kondo; Hiroki Ishihara
Journal:  Ann Transl Med       Date:  2019-12

4.  Comparable efficacy and safety between second-line and later-line nivolumab therapy for metastatic renal cell carcinoma.

Authors:  Hiroki Ishihara; Toshio Takagi; Tsunenori Kondo; Hironori Fukuda; Hidekazu Tachibana; Kazuhiko Yoshida; Junpei Iizuka; Hirohito Kobayashi; Masayoshi Okumi; Hideki Ishida; Kazunari Tanabe
Journal:  Int J Clin Oncol       Date:  2019-12-19       Impact factor: 3.402

5.  Predictive Impact of Peripheral Blood Markers and C-Reactive Protein in Nivolumab Therapy for Metastatic Renal Cell Carcinoma.

Authors:  Hiroki Ishihara; Hidekazu Tachibana; Toshio Takagi; Tsunenori Kondo; Hironori Fukuda; Kazuhiko Yoshida; Junpei Iizuka; Hirohito Kobayashi; Masayoshi Okumi; Hideki Ishida; Kazunari Tanabe
Journal:  Target Oncol       Date:  2019-08       Impact factor: 4.493

6.  Pretreatment Eosinophil Counts in Patients With Advanced or Metastatic Urothelial Carcinoma Treated With Anti-PD-1/PD-L1 Checkpoint Inhibitors.

Authors:  Jose Mauricio Mota; Min Yuen Teo; Karissa Whiting; Han A Li; Ashely M Regazzi; Chung-Han Lee; Samuel A Funt; Dean Bajorin; Irina Ostrovnaya; Gopa Iyer; Jonathan E Rosenberg
Journal:  J Immunother       Date:  2021-09-01       Impact factor: 4.912

7.  Prognostic value of pretreatment neutrophil-to-lymphocyte ratio in renal cell carcinoma: a systematic review and meta-analysis.

Authors:  Yuan Shao; Bo Wu; Wei Jia; Zikuan Zhang; Qian Chen; Dongwen Wang
Journal:  BMC Urol       Date:  2020-07-06       Impact factor: 2.264

8.  Impact of C-reactive protein flare-response on oncological outcomes in patients with metastatic renal cell carcinoma treated with nivolumab.

Authors:  Shohei Fukuda; Kazutaka Saito; Yosuke Yasuda; Toshiki Kijima; Soichiro Yoshida; Minato Yokoyama; Junichiro Ishioka; Yoh Matsuoka; Yukio Kageyama; Yasuhisa Fujii
Journal:  J Immunother Cancer       Date:  2021-02       Impact factor: 13.751

9.  Prognostic Role of Blood Eosinophil Count in Patients with Sorafenib-Treated Hepatocellular Carcinoma.

Authors:  Mario Scartozzi; Andrea Casadei-Gardini; Giulia Orsi; Francesco Tovoli; Vincenzo Dadduzio; Caterina Vivaldi; Oronzo Brunetti; Luca Ielasi; Fabio Conti; Giulia Rovesti; Laura Gramantieri; Mario Domenico Rizzato; Irene Pecora; Antonella Argentiero; Federica Teglia; Sara Lonardi; Francesca Salani; Alessandro Granito; Vittorina Zagonel; Giorgia Marisi; Giuseppe Cabibbo; Francesco Giuseppe Foschi; Francesca Benevento; Alessandro Cucchetti; Fabio Piscaglia; Stefano Cascinu
Journal:  Target Oncol       Date:  2020-12       Impact factor: 4.493

10.  Inflammatory indices and clinical factors in metastatic renal cell carcinoma patients treated with nivolumab: the development of a novel prognostic score (Meet-URO 15 study).

Authors:  Sara Elena Rebuzzi; Alessio Signori; Giuseppe Luigi Banna; Marco Maruzzo; Ugo De Giorgi; Paolo Pedrazzoli; Andrea Sbrana; Paolo Andrea Zucali; Cristina Masini; Emanuele Naglieri; Giuseppe Procopio; Sara Merler; Laura Tomasello; Lucia Fratino; Cinzia Baldessari; Riccardo Ricotta; Stefano Panni; Veronica Mollica; Maria Sorarù; Matteo Santoni; Alessio Cortellini; Veronica Prati; Hector Josè Soto Parra; Marco Stellato; Francesco Atzori; Sandro Pignata; Carlo Messina; Marco Messina; Franco Morelli; Giuseppe Prati; Franco Nolè; Francesca Vignani; Alessia Cavo; Giandomenico Roviello; Francesco Pierantoni; Chiara Casadei; Melissa Bersanelli; Silvia Chiellino; Federico Paolieri; Matteo Perrino; Matteo Brunelli; Roberto Iacovelli; Camillo Porta; Sebastiano Buti; Giuseppe Fornarini
Journal:  Ther Adv Med Oncol       Date:  2021-05-18       Impact factor: 8.168

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.