Blood Based Biomarkers as Predictive Factors for Hyperprogressive Disease

Hyperprogressive disease in patients with advanced cancer treated with immune checkpoint inhibitors

BACKGROUND

Hyperprogressive disease (HPD) is a new phenomenon developing in the era of immune checkpoint inhibitor (ICI) therapy. HPD is characterized by an unexpected and fast progression in tumor volume and poor survival. There is no standardized definition for HPD and clinicopathological variables associated with HPD are unclear. Herein, we assessed incidence, treatment outcomes and factors predictive of HPD in patients treated with ICIs.

METHODS

We retrospectively analyzed patients with advanced cancer treated with ICI at one academic center between 2014 and 2021. We used the Lo Russo's adopted criteria combined with clinical and radiologic parameters for the definition of HPD. All patients who underwent their first tumor evaluation according to RECIST1.1 were included.

RESULTS

Of 155 patients, 147 were eligible for analysis. The median age was 61 and 83% were male. The cancer types were; lung 67.3%, bladder 12.9%, gastric 9.5%, 5, colon 5.4% and renal cell carcinoma 4.8%. 59.9% of patients were treatment-naive and others had one or more lines of chemotherapy. 19 (12.9%) patients had HPD. In patients who had HPD, progression-free survival (PFS) was significantly shorter (1.5 vs 9.8 months, (HR 9.56; 95% CI (5.51-16.57), p < 0.001). The median overall survival (OS) was also shorter for HPD patients than non-HPD (3.0 vs 23.1 months, respectively, HR 12.03, 95% CI (6.64-21.81), p < 0.001). Gastric cancer, larger sum of target lesion diameters at baseline, liver metastases, higher LDH level and higher neutrophil-lymphocyte ratio (NLR) were significantly associated with HPD.

CONCLUSION

Our findings demonstrated that HPD was a rapid phenomenon with significantly poor survival rates. Several clinicopathological factors and tumor characteristics might indicate HPD.

Mean Platelet Volume to Lymphocyte Ratio: A New Biomarker Predicting Response in Patients with Solid Tumors Treated with Nivolumab

Introduction

Although immune checkpoint inhibitors (ICIs) are widely used in cancer treatment, identifying factors that predict treatment response remains a challenge in clinical practice. There is a need for biomarkers to identify patients who may not benefit from these treatments. It is crucial to identify a simple and cost-effective biomarker that can be easily incorporated into clinical practice. This study aims to investigate the mean platelet volume to lymphocyte ratio (MPVLR), as measured by a hemogram test, and median overall survival (mOS) in patients with cancer treated with nivolumab.

Methods

A total of 131 adult patients with metastatic cancer, including malignant melanoma (MM), renal cell carcinoma (RCC), non-small cell lung cancer (NSCLC), and head and neck cancer (HNC), were included in this study. Baseline demographics, ECOG (Eastern Cooperative Oncology Group) performance status, tumor type, and blood count parameters were recorded. Univariate and multivariate analyses were conducted to evaluate potential risk factors.

Results

The median age of the patients was 59.87 ± 11.97 years, and the median follow-up period was 20.20 months (IQR, 12.80-27.60). RCC (43.5%) and MM (25.9%) were the most common diagnoses. Patients with ECOG scores of 0-1 had a longer mOS than those with scores of 2-3 (mOS: 20.60 months [95% CI, 14.94-25.29] vs. 5.24 months [95% CI, 0-16.42], p < 0.001). Additionally, patients with lactate dehydrogenase (LDH) levels within the normal range had a longer mOS than those with high LDH levels (mOS: 24.54 months [95% CI, 14.13-34.96] vs. 13.10 months [95% CI, 4.49-21.72], p = 0.038). Patients with low MPVLR also had a longer mOS than those with high MPVLR (mOS: 33.70 months [95% CI, 25.99-41.42] vs. 11.07 months [95% CI, 6.89-15.24], p < 0.001). In the multivariate Cox regression analysis, high MPVLR, ECOG score of 2-3, and high LDH level were associated with shorter mOS (p < 0.001, p = 0.001, and p = 0.046, respectively).

Conclusion

This study demonstrates that MPVLR could serve as a novel biomarker for predicting response to nivolumab treatment. Incorporating MPVLR into clinical practice may aid in identifying patients who are less likely to benefit from the treatment.