BACKGROUND: Optimal prognostic and predictive biomarkers for patients with advanced-stage cancer patients who received immunotherapy (IO) are lacking. Inflammatory markers, such as the neutrophil-to-lymphocyte ratio (NLR), the monocyte-to-lymphocyte ratio (MLR), and the platelet-to-lymphocyte ratio (PLR), are readily available. The authors investigated the association between these markers and clinical outcomes of patients with advanced-stage cancer who received IO. METHODS: A retrospective review was conducted of 90 patients with advanced cancer who received treatment on phase 1 clinical trials of IO-based treatment regimens. NLR, MLR, and PLR values were log-transformed and treated as continuous variables for each patient. Overall survival (OS), progression-free survival (PFS), and clinical benefit were used to measure clinical outcomes. For univariate associations and multivariable analyses, Cox proportional-hazards models or logistic regression models were used. RESULTS: The median patient age was 63 years, and most were men (59%). The most common histologies were melanoma (33%) and gastrointestinal cancers (22%). High baseline NLR, MLR, and PLR values were associated significantly with worse OS and PFS (P < .05) and a lower chance of benefit (NLR and PLR; P < .05). Increased NLR, MLR, and PLR values 6 weeks after baseline were associated with shorter OS and PFS (P ≤ .052). CONCLUSIONS: Baseline and early changes in NLR, MLR, and PLR values were strongly associated with clinical outcomes in patients who received IO-based treatment regimens on phase 1 trials. Confirmation in a homogenous patient population treated on late-stage trials or outside of trial settings is warranted. These values may warrant consideration for inclusion when risk stratifying patients enrolled onto phase 1 clinical trials of IO agents. Cancer 2019;125:127-134.

Background Selecting the appropriate patients to receive immunotherapy (IO) remains a challenge due to the lack of optimal biomarkers. The presence of liver metastases has been implicated as a poor prognostic factor in patients with metastatic cancer. We investigated the association between sites of metastatic disease and clinical outcomes in patients receiving IO. Methods We conducted a retrospective review of 90 patients treated on IO-based phase 1 clinical trials at Winship Cancer Institute of Emory University between 2009 and 2017. Overall survival (OS) and progression-free survival (PFS) were measured from the first dose of IO to date of death or hospice referral and clinical or radiographic progression, respectively. Clinical benefit (CB) was defined as a best response of complete response (CR), partial response (PR), or stable disease (SD). Univariate analysis (UVA) and Multivariate analysis (MVA) were carried out using Cox proportional hazard model or logistic regression model. Covariates included age, whether IO is indicated for the patient’s histology, ECOG performance status, Royal Marsden Hospital (RMH) risk group, number of metastatic sites, and histology. Results The median age was 63 years and 53% of patients were men. The most common histologies were melanoma (33%) and gastrointestinal cancers (22%). Most patients (73.3%) had more than one site of distant metastasis. Sites of metastasis collected were lymph node ( n = 58 ), liver ( n = 40 ), lung ( n = 37 ), bone ( n = 24 ), and brain ( n = 8 ). Most patients (80.7%) were RMH good risk. Most patients ( n = 62 ) had received 2+ prior lines of systemic treatment before receiving IO on trial; 27 patients (30.0%) received prior ICB. Liver metastases were associated with significantly shorter OS (HR: 0.38, CI: 0.17–0.84, p = 0.017). Patients with liver metastasis also trended towards having shorter PFS (HR: 0.70, CI: 0.41–1.19, p = 0.188). The median OS was substantially longer for patients without liver metastases (21.9 vs. 8.1 months, p = 0.0048). Conclusions Liver metastases may be a poor prognostic factor in patients receiving IO on phase 1 clinical trials. The presence of liver metastases may warrant consideration in updated prognostic models if these findings are validated in a larger prospective cohort.

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BACKGROUND: Body mass index (BMI) is used to define obesity, but it is an imperfect measure of body composition. In the current study, the authors explored the association between types of fat and survival in patients treated with immunotherapy. METHODS: A retrospective analysis of 90 patients who were treated with immunotherapy on phase 1 clinical trials at the Winship Cancer Institute in Atlanta, Georgia, from 2009 through 2017 was performed. Overall survival (OS) and progression-free survival (PFS) were used to measure clinical outcomes. Baseline BMI and radiographic images at the middle of the third lumbar vertebrae were obtained. Fat densities were calculated and converted to indices (subcutaneous fat index [SFI], intermuscular fat index [IFI], and visceral fat index [VFI]) after dividing by height in meters squared. Risk groups were created using recursive partitioning and the regression trees method for SFI and IFI, which were selected by stepwise variable selection among all fat-related variables. The Cox proportional hazards model and Kaplan-Meier method were used for the association with OS and PFS. RESULTS: The majority of patients (59%) were male and diagnosed with melanoma (33%) or gastrointestinal cancers (22%). The median BMI was 27.4 kg/m 2 , the median SFI was 62.78, the median IFI was 4.06, and the median VFI was 40.53. Low-risk patients (those with an SFI ≥73) had a significantly longer OS (hazard ratio, 0.20; 95% CI, 0.09-0.46 [P < .001]) and PFS (hazard ratio, 0.38; 95% CI, 0.20-0.72 [P = .003]) compared with patients at intermediate risk (those with an SFI <73 and IFI <3.4) and poor risk (those with an SFI <73 and IFI ≥3.4). The Uno concordance statistics were found to be higher for fat risk groups than BMI in predicting OS (0.603 vs 0.574; P = .581) and PFS (0.602 vs 0.586; P = .71). CONCLUSIONS: Increased BMI, increased SFI, and decreased IFI may be associated with prolonged survival in patients with cancer who are treated with immunotherapy. Further studies are needed to elucidate the effect of adiposity on the host immune response to immunotherapy. Cancer 2020;126:575-582.