Renal cell carcinoma (RCC) accounts for 2% to 3% of all malignant disease in adults, representing the seventh most common cancer in men and tenth most common cancer in women in the United States [1]. In Korea, RCC holds the tenth rank of incidence, regardless of age and sex, and the burden of RCC will continue to grow as Korea’s population ages [2]. The current World Health Organization classification system for RCC includes various tumor subtypes, where the major histologic variants are clear cell RCC (75% to 90% of tumors), papillary RCC (10% to 15%), and chromophobe RCC (4% to 5%) [3,4]. In the case of clear cell RCC, the von Hippel Lindau (VHL) gene is inactivated in 80% to 90% of patients [5]. Plus, since the vascular endothelial growth factor (VEGF) and mammalian target of rapamycin pathways are important for this subtype, most previous randomized phase III clinical trials of targeted therapy have focused on patients with the clear cell histologic subtype [6-10]. Meanwhile, due to the relatively low prevalence of non-clear cell RCC, the optimal treatment and role of targeted agents for this patient group remain uncertain and under investigation. When Hudes et al. [10] compared the efficacy and safety of temsirolimus and interferon-α, they confirmed the benefit of temsirolimus for both poor-risk clear cell RCC and non-clear cell RCC. However, this is the only reported phase III trial that included patients with non-clear cell histology and these patients represented less than 20% of the total study group.

For metastatic RCC, various prognostic scoring systems have already been developed to define patient risk groups based on combining independent prognostic factors for survival outcomes [11]. The most widely used prognostic factor model is from the Memorial Sloan-Kettering Cancer Center (MSKCC) [12,13]. However, while the MSKCC model has been externally validated and is commonly used for clinical trial stratification, it is not as relevant for predicting survival in the era of immunotherapy [14]. Thus, in response to the need for new prognostic models in the era of VEGF-targeted therapies, Heng et al. [15,16] identified six prognostic factors: low hemoglobin level (< lower limit of normal), high level of corrected serum calcium (> 10 mg/dL), Karnofsky performance status (KPS, < 80%), a time from initial diagnosis to initiation of therapy of less than 1 year, high absolute neutrophil count (> upper limit of normal), and high platelet count (> upper limit of normal). This International Metastatic RCC Database Consortium (IMDC) model has already been proven useful as a prognostic tool in major clinical trials of novel targeted therapies [15,16]. Moreover, the IMDC model has even shown a better concordance index for patients with non-clear cell histologies [17,18]. Meanwhile, the Global Advanced Renal Cell Carcinoma (ARCC) pivotal study included six different variables: high serum lactate dehydrogenase (LDH) level (1.5 times the upper limit of normal), low hemoglobin level (< lower limit of normal), high level of corrected serum calcium (> 10 mg/dL), a time from initial diagnosis to initiation of therapy of less than 1 year, KPS (< 60%), and metastases in multiple organs [10].

Notwithstanding, the three most commonly used tools (MSKCC, IMDC, and ARCC models) were mainly developed based on patient cohorts with heterogeneous ethnic identity and clear cell histology treated with several targeted agents. Accordingly, this study compared the applicability of these three risk stratification models in the case of a homogenous Korean patient cohort treated with temsirolimus as the first-line therapy for non-clear cell RCC.

This study comprehensively compared the prognostic utility of commonly used prognostic models in Korean non-clear cell RCC patients treated with temsirolimus as the first-line therapy. All the prognostic tools functioned well in terms of stratifying the non-clear cell RCC patients into risk groups with significantly different survival outcomes. In particular, the ARCC risk model showed relatively higher accuracy for predicting survival than the other two models. The non-clear cell RCC patients also showed inferior survival outcomes, consistent with previous studies [11].

The prognostic factors can be divided into four general groups: those associated with PS, tumor burden, systemic inflammatory markers, and treatment-related factors [20]. The PS is assessed using the Eastern Cooperative Oncology Group or KPS scales. The presence of constitutional symptoms, multiple sites of metastasis, level of LDH, and the presence of bone or liver metastasis have all been associated with a high tumor burden. Additionally, several proinflammatory response markers, including the erythrocyte sedimentation rate, C-reactive proteins, and neutrophilia, have also been identified as prognostic factors in cancer patients. The MSKCC, IMDC, and ARCC risk models use all these prognostic factors in different ways. In the case of the IMDC model, instead of the traditional elevated LDH level and nephrectomy status, it includes inflammation markers related to the overproduction of cytokines (neutrophilia and thrombocytosis). Moreover, in the current study, the IMDC model accurately predicted the prognosis of the non-clear cell RCC patients treated with temsirolimus as the first-line therapy. Kroeger et al. [18] also recently showed the reliability of the IMDC prognostic model for predicting OS and time to treatment failure in non-clear cell RCC patients. However, in their study, only 7% (n = 39) of the patients were treated with temsirolimus as their first-line therapy, and the non-clear RCC subtypes were not reported.

Interestingly, among the investigated scoring systems, the ARCC risk model produced the highest predictive values for the current patient population. The NCCN guidelines for RCC list six predictors of short survival when selecting patients for treatment with temsirolimus, and these poor prognostic features were defined in the Global ARCC trial [10,21]. In that trial, 80% of the patients (n = 502) had clear cell histology, and three or more poor prognostic factors were present in 94% (n = 589) of the patients. However, according to the MSKCC risk classification, only 74% (n = 462) of the patients were assigned to the poor risk group, indicating that some patients in the ARCC poor-risk group were considered intermediate by the MSKCC criteria. The unique differential feature of the ARCC model is the presence of organ metastasis. This factor of poor prognosis for patients with an increased tumor burden in RCC has already been described in a number of studies [14,15]. The current study also found multiple organ metastases in 79.7% of the patients. Thus, organ metastasis would appear to be a powerful tool for predicting the clinical outcomes for such patients.

Consistent with previous studies, the current study found an ORR of 8.2% and a DCR of 48.7%. In addition, the non-clear cell RCC patients had a shorter PFS and OS at 3 and 8 months, respectively [22]. The Global ARCC trial showed that temsirolimus significantly improved OS when compared with interferon-α in poor-risk metastatic RCC patients (10.9 months vs. 7.3 months). However, 80% of the patients had clear cell histology, and the histologic subtypes were not reported. While the current data have certain limitations, including its retrospective nature and a relatively small study sample, the advantages of the current study are as follows: (1) patient cohort with Korean homogenous ethnic identity, (2) patient cohort with non-clear cell histology, and (3) equivalent treatment application.

In conclusion, all three risk models reliably prognosticated the clinical outcomes of the non-clear cell RCC patients treated with temsirolimus as the first-line therapy. Furthermore, the ARCC risk model performed better than the other risk models in predicting survival. Further studies are needed to confirm these findings.