Assessing the prognostic value of IMDC risk score for nivolumab-treated patients with renal cancer and malignant melanoma

Abstract

BACKGROUND:

The response of Renal Cell Cancer (RCC) to tyrosine kinase inhibitors (TKI) has been well established. Although these stratifications have been established for TKI response and prognosis, these parameters have recently been used to predict immunotherapy response in RCC. We aimed to use a combination of clinical parameters of International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) risk groups and metastatic sites at the time of diagnosis to predict the effectiveness of immune checkpoint inhibitors in malignant melanoma (MM).

METHOD:

In this cross-sectional study, we retrospectively analyzed the demographic information, metastatic sites, and IMDC risk group data. The blood parameters were included in the first cycle of nivolumab treatment.

RESULTS:

The OS was statistically different between the RCC and MM groups in terms of the IMDC. In univariate analysis of stage at diagnosis, CRP levels and bone and bone marrow metastases were confirmed to be prognostic factors in the MM population in terms of OS. Brain metastasis was a prognostic factor for RCC, whereas sex, line of treatment, LDH, bone, and splenic metastasis remained significant in patients with MM in terms of OS. Brain metastasis was prognostic in both cancer types in multivariate analysis in terms of PFS. In addition to brain metastasis, LDH levels and lung, liver, and splenic metastases also affect PFS in patients with MM undergoing nivolumab treatment.

CONCLUSION:

In our study, the IMDC was confirmed to be a prognostic factor for MM. The IMDC groups were similar, except for the favorable RCC and MM groups. Different metastatic sites were prognostic, similar to the IMDC risk group in the MM group.

Keywords

IMDC risk group malign melanoma Immunotherapy nivolumab metastatic sites renal cell carcinoma

1. Introduction

Immune system and tumor-driven inflammation are important hallmarks of cancer [1]. Genetic instability, angiogenesis, and cell growth have been suggested to be the main sources of chemokines and cytokines related to chronic inflammation. Cytotoxic T and B cells, which are influenced by these mediators, play a major role in the detection of tumors and elimination of cancer cells [2, 3, 4, 5].

Risk stratification due to the clinical characteristics of patients is used for prognostic evaluation of renal cell cancer (RCC). The response to tyrosine kinase inhibitors (TKI) in RCC has been well established over a long period [6, 7]. Although these stratifications have been established for TKI response and prognosis, these parameters have recently been used to predict immunotherapy response in RCC. In a recent trial, the combination of nivolumab and ipilimumab showed a superior response to sunitinib in intermediate- and poor-risk RCC groups [8]. Although two more trials have used these risk stratifications for immunotherapy and tyrosine kinase inhibitor combinations, the possible imbalance in TKIs may decrease the value of clinical factors [9, 10]. International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) risk groups may have expanded their use to different cancer types receiving immunotherapy and TKI.

The immune system is another aspect of the immune response of malignant cells [11, 12]. As well as tumor-infiltrating lymphocytes, peripheral immune cells are important for predicting immunotherapy response. Ferrucci et al. reported that baseline increased absolute neutrophil counts correlated with decreased overall survival (OS) and progression-free survival (PFS) in metastatic malignant melanoma treated with ipilimumab [13].

C-reactive protein (CRP) that is induced by IL-6 may show an immunotherapeutic response. In metastatic RCC patients whose CRP levels remain high after nephrectomy, poorer outcomes have been reported with INF- $\alpha$ treatment. Although the number of comparative groups was low, CRP levels may have a predictive role in the immunotherapy response [14]. In addition, Sasaki et al. reported that neutrophile to lymphocyte ratio (NLR), lactate dehydrogenase (LDH), and CRP levels are predictive factors for hyperprogression in metastatic gastric cancer patients treated with nivolumab monotherapy [15]. Elevated LDH levels are speculated to prevent the effects of anti-PD1/PD-L-1 antibodies and are associated with a poor prognosis [16, 17].

The Royal Marsden Hospital (RMH) scoring system, combining albumin, LDH levels, and the number of metastatic sites, showed a predictive effect on survival in multiple cancer types in phase 1 trials [18, 19]. This scoring system has not yet been tested as an immunotherapeutic agent. Previous studies have shown decreased survival in patients with breast, bladder, and colorectal cancers with liver metastasis [20, 21, 22].

With these developments and further understanding, the cancer-immune system relationship may force us to use dynamic nomograms to select patients who will benefit from immune checkpoint inhibitors. In this study, we aimed to use a combination of the clinical parameters of IMDC risk groups and metastatic sites at the time of diagnosis to predict both the effectiveness and detrimental effects of immune checkpoint inhibitors in patients receiving nivolumab for malignant melanoma (MM) and RCC.

2. Material method

Figure 1.

The flowchart of the study: Study population selection and the parameters evaluated were shown.

2.1 Patients

This cross-sectional study retrospectively analyzed the archives of the Antalya Education and Research Hospital Medical Oncology clinic between 2016–2022. Of 146 patients, 92 who received nivolumab between 2018–2022 were included in the study. Patients who received nivolumab and had adequate follow-up, clinical information, and laboratory parameters with appropriate imaging for the evaluation of treatment response were included in the study. Patients who lacked clinical parameters in the IMDC risk and follow-up groups were also excluded [6]. Karnofsky score component was converted from the patients’ data of the Eastern Cooperative Oncology Group (ECOG) Performance Score (PS), which is more utilized in current practice [23, 24]. Demographic information, metastatic sites, IMDC risk group data, CRP levels, diagnosis, treatment initiation and progression, and the last control times were recorded. In addition, the total number of treatment lines and the nivolumab line of treatment (LOT) were recorded. The blood parameters were included in the first cycle of nivolumab treatment (Fig. 1).

2.2 Statistical analysis

Statistical analyses were performed using SPSS software (Statistical Package for the Social Sciences, version 22.0. SPSS Inc, Chicago, IL, USA). The Kolmogorov-Smirnov test was used to determine whether the data conformed to a normal distribution. Descriptive data are presented as either means or medians for continuous variables, and frequencies and percentages are reported for categorical variables. Kaplan-Meier curves were used to determine the differences in survival. Chemotherapy responses were defined based on radiological reports. Differences between groups were tested using the chi-square test. Cox regression analysis was performed to evaluate prognostic factors. These factors cannot converge or be outfitted from the analysis. The cutoff values of prognostic factors determined both the IMDC categorization and ROC analysis.

2.3 Ethics

This study was approved by the local ethics committee of Antalya Education and Research Hospital, and the trial was conducted in accordance with the principles of the Declaration of Helsinki.

3. Results

Table 1
The comparative characteristics of the study population according to diagnosis. There were statistical difference in four categories: Stage at diagnosis, line of treatment, total lines of treatment received and IMDC groups

Features	Renal cell carcinoma ( $n$ :48)		Malign melanoma ( $n$ :44)		$p$ -value
Age	Mean	Median	Mean	Median
(years)	63.5	65	62.2	61.5	0.38 ${}^{1}$
Gender	Male	Female	Male	Female
( $n$ )	35	13	32	12	0.98
ECOG PS	0 / 1 / 2		0 / 1 / 2
( $n$ )	0 / 33 / 15		4 / 26 / 14		0.09
Smoking duration	Mean	Median	Mean	Median
(years)	20.1	22.5	19.4	24.5	0.83
Stage at diagnosis	1 / 2 / 3 / 4		1 / 2 / 3 / 4
( $n$ )	2 / 16 / 7 ${}^{*}$ / 13		0 / 13 / 18 ${}^{*}$ /13		0.03
Time to treatment	Less than 1 year	More than 1 year	Less than 1 year	More than 1 year
( $n$ )	22	26	18	26	0.63
Total Line of Treatment	1 / 2 / 3 / 4 / 5		1 / 2 / 3 / 4 / 5
( $n$ )	0 ${}^{}$ /12 ${}^{}$ /30 ${}^{*}$ /3/3		5 ${}^{}$ /35 ${}^{}$ /4 ${}^{*}$ /0/0		$<$ 0.001
Line of Nivolumab	1 / 2 / 3 / 4		1 / 2 / 3 / 4
( $n$ )	0 ${}^{}$ /13 ${}^{}$ /33 ${}^{*}$ /2		5 ${}^{}$ /35 ${}^{}$ /4 ${}^{*}$ /0		$<$ 0.001
Lung Metastasis	Negative	Positive	Negative	Positive
( $n$ )	15	33	14	29	0.77
Lymph Node Metastasis	Negative	Positive	Negative	Positive
( $n$ )	8	40	3	41	0.14
Liver Metastasis	Negative	Positive	Negative	Positive
( $n$ )	35	16	36	8	0.31
Bone metastasis	Negative	Positive	Negative	Positive
( $n$ )	28	20	31	13	0.22
Brain Metastasis	Negative	Positive	Negative	Positive
( $n$ )	43	5	37	7	0.43
Bone Marrow Metastasis	Negative	Positive	Negative	Positive
( $n$ )	48	0	43	1	0.29
Splenic Metastasis	Negative	Positive	Negative	Positive
( $n$ )	47	1	43	1	0.95
Hemoglobin	Mean	Median	Mean	Median
g/dl	10.6	10.8	10.6	10.6	0.84 ${}^{1}$
Neutrophile	Mean	Median	Mean	Median
n/ul	2716	2750	3281	2650	0.82 ${}^{1}$
Platelet	Mean	Median	Mean	Median
n/ul	407687	332000	303795	314000	0.19¶
Calcium	Mean	Median	Mean	Median
mg/dl	8.7	8.6	8.5	8.4	0.12 ${}^{1}$
Albumin	Mean	Median	Mean	Median
g/dl	3.23	3.20	3.28	3.20	0.97 ${}^{1}$
LDH	Mean	Median	Mean	Median
mg/dl	337	321	314	317	0.83 ${}^{1}$
CRP	Mean	Median	Mean	Median
mg/dl	46.3	44.5	47.4	37.0	0.99 ${}^{1}$
IMDC score	0/1/2/3/4		0/1/2/3/4
( $n$ )	0 ${}^{*}$ /17/14/14/3		5 ${}^{*}$ /15/9/12/3		0.18
IMDC group	Fav / Int/ Poor		Fav / Int/ Poor
( $n$ )	0 ${}^{*}$ /31/17		5 ${}^{*}$ /24/15		0.054

${}^{*}$ Statistical difference in post-hoc analysis; ¶: parametric test; ${}^{1}$ : non-parametric test; Fav: Favorable group; Int: Intermediate group; Poor: Poor group; LDH: Lactate Dehydrogenase; CRP: C-reactive protein.

3.1 Comparative analysis of study population

One-hundred forty-six patients who received nivo-lumab were retrospectively analyzed, and 92 patients were enrolled. There were 48 patients with RCC and 44 with MM. The median ages of the patients with RCC and MM were 65 and 61.5 years respectively. Male dominance was observed in both groups with no statistical differences. There was no difference in the ECOG performance scores between the groups ( $p=$ 0.09). The stage at diagnosis was higher in the MM group than that in the RCC group ( $p=$ 0.03). Also, the total line of treatment and line of nivolumab were statistically different between the groups ( $p<$ 0.001). There was no difference between RCC and MM in terms of metastatic pattern. The lung, liver, bone, brain, bone marrow, and spleen metastases were similar. Although the IMDC scores were similar between the groups, IMDC groups were different. None of the patients in the MM group were considered to have RCC, while 5 patients were considered to have a favorable risk ( $p=$ 0.05). The comparative characteristics of the study populations are described in Table 1. The median follow-up duration was 28 months for the study population. CRP levels were categorized to determine the optimal levels for identifying biomarkers for immunotherapy. ROC analysis showed 36 mg/dl with 78% sensitivity and 78% specificity.

Figure 2.

The Kaplan-Meier curves of RCC patients according to IMDC groups for OS. A statistically significant difference was observed between three groups. The median OS was not reached in intermediate IMDC group.

Figure 3.

The Kaplan-Meier curves of MM patients according to IMDC groups for OS. A statistically significant difference was observed between three groups. The median OS was not reached in good IMDC group.

Table 2

The univariate analysis of the study population according in terms of PFS according to diagnosis. Gender, IMDC group in RCC and bone marrow metastasis in MM were statistically significant

Features	Renal cell carcinoma		Malign melanoma
	Hazard ratio	$p$ -value	Hazard ratio	$p$ -value
Gender	0.44	0.05	0.52	0.10
Stage at diagnosis	$-$	0.25	$-$	0.92
IMDC group	0.30 ${}^{}$*	0.002	$-$	0.41
Lung met.	0.52	0.07	0.85	0.70
Lymph node met.	1	0.99	0.29	0.18
Liver met.	1.89	0.08	0.55	0.19
Brain met.	1.92	0.15	0.57	0.19
Bone met.	0.68	0.27	1.74	0.14
Bone marrow met.	N/A	N/A	13.1	0.005
Spleen met.	4.75	0.09	0.35	0.22
LOT	$-$	0.30	$-$	0.40
Total number of treatments	$-$	0.45	$-$	0.59
CRP category	1.37	0.37	1.65	0.19

Met: Metastasis; CRP: C Reactive Protein; LOT: Line of Treatment; ${}^{*}$ Subgroup HR.

Table 3

The univariate analysis of the study population according in terms of OS according to diagnosis. IMDC groups, CRP category, lung and spleen metastasis in RCC and IMDC groups, stage at the diagnosis, CRP category, bone and bone marrow metastasis were statistically significant

Features	Renal cell carcinoma		Malign melanoma
	Hazard ratio	$p$ -value	Hazard ratio	$p$ -value
Gender	1.28	0.52	1.39	0.40
Stage at diagnosis	$-$	0.60	0.29 ${}^{}$*	0.05
IMDC group	0.21	$<$ 0.001	0.39/0.17 ${}^{}$*	0.006
Lung met.	2.31	0.025	0.55	0.16
Lymph node met.	1.47	0.38	0.53	0.52
Liver met.	0.59	0.17	0.86	0.74
Brain met.	0.46	0.14	0.94	0.90
Bone met.	0.54	0.10	0.42	0.03
Bone marrow met.	N/A	N/A	0.02	$<$ 0.001
Spleen met.	0.11	0.012	0.85	0.87
LOT	$-$	0.26	$-$	0.19
Total number of treatments	$-$	0.63	$-$	0.10
CRP category	0.24	0.001	0.21	$<$ 0.001

Met: Metastasis; CRP: C Reactive Protein; LOT: Line of Treatment; ${}^{*}$ Subgroup HR.

3.2 Survival analysis

The OS was statistically different between the RCC and MM groups in terms of the IMDC (Figs 2, 3) ( $p<$ 0.001; $p=$ 0.006). In MM patients the median OS time for intermediate and poor group were 20 and 5 months respectively. In good prognosis group median survival time was not reached. For RCC patients, the median time of survival for the intermediate group was not reached, while that for the poor prognostic group was 4 months. In univariate analysis, IMDC groups, stage at diagnosis, CRP levels, and bone and bone marrow metastases were confirmed to be prognostic factors in the MM population in terms of OS. The median OS times for stages 3 and 4 were 8 and 5 months, respectively, whereas the median survival time was not reached in stage 2 ( $p=$ 0.006, $p=$ 0.05, $p<$ 0.001, $p=$ 0.03, and $p<$ 0.001, respectively). Patients with bone metastasis patients had 6 months OS, whereas those without bone metastasis had a median OS of 25 months. In the RCC population, IMDC groups, CRP levels, and lung and spleen metastases were confirmed to be prognostic factors for OS ( $p<$ 0.001; $p<$ 0.001; $p=$ 0.02; $p=$ 0.01). High CRP levels had 9 months median OS while low CRP groups’ median OS cannot be reached. In terms of lung metastasis, patients with metastasis had better survival at 30 months than at 9 months. The absence of splenic metastasis was correlated with better survival at 14 and 1 month (Tables 2 and 3).

Figure 4.

The Kaplan-Meier curves of RCC patients according to IMDC groups for PFS. Border-line statistical significance was observed between groups.

Figure 5.

The Kaplan-Meier curves of MM patients according to IMDC groups for PFS. No statistical difference was observed.

In terms of PFS, sex and IMDC were predictive factors in the RCC group, whereas only bone marrow metastasis was statistically significant in the MM group. The median PFS times for the intermediate and poor prognostic groups were 5 and 2 months, respectively ( $p=$ 0.05; $p=$ 0.002; $p=$ 0.05). Males and females had 3 and 2 months of PFS in RCC respectively. In patients with bone marrow metastasis, the median PFS was shorter than 1 month, while the lack of bone marrow metastasis was related to 3 months of PFS in MM. The Kaplan-Meier curves for PFS in terms of IMDC risk groups are shown in Figs 4 and 5.

Table 4

The multivariate analysis of the study population according in terms of OS according to diagnosis. Brain metastasis in RCC and gender, bone metastasis, LDH levels and total lines of treatment in MM were statistically significant

Features	Renal cell carcinoma		Malign melanoma
	Hazard ratio	$p$ -value	Hazard ratio	$p$ -value
Age	0.9	0.09	1.03	0.19
Gender	2.5	0.16	0.16	0.053
Stage at diagnosis	$-$	0.58	$-$	0.48
IMDC group	0.25	0.07	$-$	0.07
Lung met.	1	0.98	2.6	0.15
Lymph node met.	1.4	0.43	3.8	0.28
Liver met.	0.34	0.14	4.6	0.07
Brain met.	0.09	0.006	2.1	0.21
Bone met.	0.55	0.41	0.22	0.017
Bone marrow met.	NA	NA	NA	NA
Spleen met.	0.02	0.06	44	0.02
LDH	0.99	0.44	1.02	0.001
LOT	$-$	0.97	$-$	0.02
Total number of treatments	$-$	0.99	$-$	0.85
CRP category	0.18	0.16	0.53	0.30

Met: Metastasis; CRP: C Reactive Protein; LDH: Lactate Dehydrogenase; LOT: Line of Treatment.

Table 5

The multivariate analysis of the study population according in terms of PFS according to diagnosis. Brain metastasis in RCC and LDH levels, lung, liver, brain, and spleen metastasis in MM were statistically significant

Features	Renal cell carcinoma		Malign melanoma
	Hazard ratio	$p$ -value	Hazard ratio	$p$ -value
Age	0.95	0.19	1.02	0.34
Gender	2.4	0.21	0.46	0.35
Stage at diagnosis	$-$	0.92	$-$	0.92
IMDC group	$-$	0.06	$-$	0.34
Lung met.	2.5	0.36	5.3	0.03
Lymph node met.	2	0.48	2.3	0.67
Liver met.	0.19	0.07	11	0.01
Brain met.	0.07	0.008	4.63	0.047
Bone met.	1.3	0.77	1.2	0.70
Bone marrow met.	NA	NA	0.34	0.53
Spleen met.	0.64	0.82	978	0.002
LDH	0.99	0.27	1.01	0.008
LOT	$-$	0.08	$-$	0.19
Total number of treatments	$-$	0.93	$-$	0.99
CRP category	1.7	0.66	0.57	0.49

Met: Metastasis; CRP: C Reactive Protein; LDH: Lactate Dehydrogenase; LOT: Line of Treatment.

Multivariate analysis of the study population according to OS and PFS according to diagnosis is shown in Tables 4 and 5, respectively. In terms of OS, brain metastasis was a prognostic factor for RCC, whereas sex, LOT, LDH, bone, and splenic metastasis remained significant in MM patients.

Brain metastasis was predictive of both cancer types in the multivariate analysis in terms of PFS. In addition to brain metastasis, LDH levels and lung, liver, and splenic metastases also affect PFS in patients with MM undergoing nivolumab treatment. These parameters were confirmed to be independent predictive factors for nivolumab treatment in patients with MM.

4. Discussion

To our knowledge, this is the first study to evaluate IMDC risk score in combination with metastatic sites in patients with different cancer types receiving immunotherapy. In our study, although the components of the IMDC groups were similar between patients with RCC and MM, there was a difference in the IMDC scores and groups between diagnoses. In contrast, the IMDC group was associated with better prognosis in terms of OS in both RCC and MM.

There has been increased effort to understand the relationship between tumors and the immune system. Some studies have attempted to establish immunograms for patients receiving immunotherapies [25]. Baseline peripheral blood parameters were evaluated in patients with lung cancer who received nivolumab. Immunotherapy response may be more related to the immune response than tumor type [26]. For patients receiving nivolumab compared to non-small cell lung cancer and RCC, increased neutrophil-to-lymphocyte ratio at the 6 ${}^{\text{th}}$ week was related to poor prognosis. This literature strengthens the hypothesis of the dynamic effects of immune responses on the prognosis of patients with cancer [27]. IMDC risk score had a great impact on RCC studies combining TKI and immunotherapy, showing prognostic and predictive effects. Although the predictive effect was not determined for the avelumab plus axitinib combination, pembrolizumab plus axitinib failed in the favorable group [9, 10]. The dynamic process between the tumor and immune system makes it difficult to identify patients who will benefit from treatment. The clinical parameters of the patients with cancer were rigorously investigated. This is especially true after the use of immunotherapy in patients with cancer [28]. There are multiple factors in RCC that affect immunotherapy response differently than in the IMDC group. In one study, the modified Glasgow Prognostic Score, which is composed of albumin and CRP, was evaluated and confirmed to be prognostic in patients with RCC receiving monotherapy with immune checkpoint inhibitors [29]. Negishi et al. investigated nivolumab response in RCC in different organ metastases. The study showed a worse response in bone metastasis than in lung and liver metastases. Although the response rates were low, the median PFS was longer in patients with bone and lymph node metastases than in those with lung and liver metastases [30]. In a different study, metastatic sites were confirmed to be prognostic factors in non-small cell lung cancer receiving nivolumab. Liver and lung metastases were related to shorter PFS, independent of the histological subtype [31]. Also, retreatment with immunotherapy in patients with MM may be related to response [32]. In our study, splenic metastasis for MM and brain metastasis for both diseases were predictive of PFS in multivariate analysis. Brain metastasis for RCC and splenic and bone metastases for MM were prognostic factors in terms of OS. No specific response was available for any organ in our study. Most studies have investigated the individual risk factors. There may be different immunological infiltrations and responses at different organ sites. In a study that investigated the ipilimumab plus nivolumab combination in malignant melanoma, eosinophile, basophile, NLR, and LDH levels were confirmed to be independent prognostic factors [28]. Similar to this study, LDH levels were related to the prognosis in our study group. Although this study evaluated the combination of immunotherapy in patients with MM, LDH levels may still be a valuable prognostic factor in patients receiving single-agent immunotherapy. In another study, 16 markers were investigated in patients receiving immunotherapy, and low-density lipoprotein (LDL), CRP, free androgen index levels, lymphocytes, basophil, PD1 positive monocyte counts, and hemoglobin levels were reported to be related to PFS [33]. In a small study evaluating nivolumab response in patients, CRP levels and erythrocyte sedimentation rates were statistically different. These parameters changed during treatment and had a predictive effect. This study speculated that high inflammation influenced the immunotherapy response [34]. Also, Nakamura et al. showed that serum LDH and CRP levels are prognostic markers in patients with metastatic MM treated with nivolumab [35]. In contrast, metastatic sites were more significant than metabolic parameters in terms of PFS in our study. Metabolic parameters, such as LDH and CRP levels, in the IMDC risk group were related to the prognosis of OS in univariate and multivariate analyses. Androgen levels are related to lipid metabolism and hematological markers, which may be important for future immunograms.

Likewise, peripheral blood parameters and metastatic organs are important in determining patient prognosis. Although this is a highly investigated area, there is still a lack of literature on patients receiving immunotherapy. In a study in which phase 1 study of patients, liver metastasis was reported to have a significantly shorter OS and a trend toward shorter PFS. Although one-third of the study population included patients with MM, a subgroup analysis reported outcomes [36]. Different to this study, we found that metastatic sites had more prognostic effects, especially in patients with MM receiving nivolumab. In addition, the RMH score, which included the number of metastatic sites, was used in this study [36]. We did not determine the number of metastatic sites in this study.

4.1 Limitations

The study was retrospectively designed to limit data quality. Additionally, the study population was too small to identify certain factors. Bone marrow metastasis was excluded from the proper analysis using Cox regression. Although the number of treatments and the line of nivolumab were added to the statistics, the difference in the treatment of these diseases was underestimated. A comparison was made between the study groups; however, there was an imbalance in some factors were imbalanced. The PDL-1 status was not available for the study population.

5. Conclusion

In our study, the IMDC was confirmed to be a prognostic factor for MM. The IMDC groups were similar except for the favorable RCC and MM groups. Different metastatic sites were prognostic, similar to the IMDC risk group in the MM group. A combination of immune subsets with metabolic and clinical factors may be less prone to failure and have the potential to provide new or currently used predictive scores. The validity of combined scores should be tested in larger studies with clearly defined patient groups.

Footnotes

Acknowledgments

This study did not receive any funding from commercial or non-commercial organizations. The study database is available on demand.

Conflict of interest

The authors declare no conflict of interest.

Author contributions

Conception: IB.

Interpretation or analysis of data: AHO, YS, and IB.

Preparation of the manuscript: IB.

Revision for important intellectual content: AHO, YS, and IB.

Supervision: IB.

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Assessing the prognostic value of IMDC risk score for nivolumab-treated patients with renal cancer and malignant melanoma

Abstract

BACKGROUND:

METHOD:

RESULTS:

CONCLUSION:

Keywords

1. Introduction

2. Material method

2.2 Statistical analysis

2.3 Ethics

3. Results

Table 1 The comparative characteristics of the study population according to diagnosis. There were statistical difference in four categories: Stage at diagnosis, line of treatment, total lines of treatment received and IMDC groups

4.1 Limitations

5. Conclusion

Footnotes

Acknowledgments

Conflict of interest

Author contributions

References

Table 1
The comparative characteristics of the study population according to diagnosis. There were statistical difference in four categories: Stage at diagnosis, line of treatment, total lines of treatment received and IMDC groups