The predictive role of hematologic markers in resectable NSCLC patients treated with neoadjuvant chemoimmunotherapy: a retrospective cohort study

Prognostic significance of hemoglobin, albumin, lymphocyte, and platelet (HALP) score in breast cancer: a propensity score-matching study

BACKGROUND

The hemoglobin-albumin-lymphocyte-platelet (HALP) score functions as a comprehensive index that assesses the systemic inflammatory response, nutritional, and immune status. This study aimed to explore the relationship between preoperative HALP score and the prognosis of BC patients and to develop predictive nomograms.

METHODS

Clinicopathological data were collected for BC patients who underwent mastectomy between December 2010 and April 2014 from Sun Yat-sen University Cancer Center. The optimal cutoff value for HALP was determined by maximally selected rank statistics for overall survival data. Propensity score matching (PSM) was applied to develop comparable cohorts of high-HALP group and low-HALP group. Kaplan-Meier curves and Cox regression analyses were performed to determine the impact of HALP on BC patients. Prognostic nomograms were developed based on the multivariate Cox regression method. Then, the concordance index (C-index), calibration plots, and decision curves analysis (DCA) were applied to evaluate the prognostic performance of the nomograms.

RESULTS

A total of 1,856 patients were included as the primary cohort, and 1,470 patients were matched and considered as the PSM cohort. In the primary cohort, the 5-year overall survival (OS) and progression-free survival (PFS) rates for high-HALP group (≥ 47.89) and low-HALP group (< 47.89) were 94.4% vs. 91.0% (P = 0.005) and 87.8% vs. 82.1% (P = 0.005), respectively. Similar results were observed in PSM cohort (5-year OS, 94.3% vs. 90.8%, P = 0.015; 5-year PFS, 87.5% vs. 83.2%, P = 0.036). Notably, multivariate Cox regression analysis in the PSM cohort showed that HALP could independently predict BC patient prognosis in both OS (HR: 0.596, 95%CI [0.405-0.875], P = 0.008) and PFS (HR: 0.707, 95%CI [0.538-0.930], P = 0.013). OS and PFS nomograms showed excellent predictive performance with the C-indexes of 0.783 and 0.720, respectively. The calibration plots and DCA also indicated the good predictability of the nomograms. Finally, subgroup analysis further demonstrated a favorable impact of HALP on both OS and PFS.

CONCLUSION

Preoperative HALP score can be used as a reliable independent predictor of OS and PFS in BC patients, and the nomograms may provide a personalized treatment strategy.

Association between pretreatment emotional distress and immune checkpoint inhibitor response in non-small-cell lung cancer

Emotional distress (ED), commonly characterized by symptoms of depression and/or anxiety, is prevalent in patients with cancer. Preclinical studies suggest that ED can impair antitumor immune responses, but few clinical studies have explored its relationship with response to immune checkpoint inhibitors (ICIs). Here we report results from cohort 1 of the prospective observational STRESS-LUNG study, which investigated the association between ED and clinical efficacy of first-line treatment of ICIs in patients with advanced non-small-cell lung cancer. ED was assessed by Patient Health Questionnaire-9 and Generalized Anxiety Disorder 7-item scale. The study included 227 patients with 111 (48.9%) exhibiting ED who presented depression (Patient Health Questionnaire-9 score ≥5) and/or anxiety (Generalized Anxiety Disorder 7-item score ≥5) symptoms at baseline. On the primary endpoint analysis, patients with baseline ED exhibited a significantly shorter median progression-free survival compared with those without ED (7.9 months versus 15.5 months, hazard ratio 1.73, 95% confidence interval 1.23 to 2.43, P = 0.002). On the secondary endpoint analysis, ED was associated with lower objective response rate (46.8% versus 62.1%, odds ratio 0.54, P = 0.022), reduced 2-year overall survival rate of 46.5% versus 64.9% (hazard ratio for death 1.82, 95% confidence interval 1.12 to 2.97, P = 0.016) and detriments in quality of life. The exploratory analysis indicated that the ED group showed elevated blood cortisol levels, which was associated with adverse survival outcomes. This study suggests that there is an association between ED and worse clinical outcomes in patients with advanced non-small-cell lung cancer treated with ICIs, highlighting the potential significance of addressing ED in cancer management. ClinicalTrials.gov registration: NCT05477979 .

Potential predictors of the pathologic response after neoadjuvant chemoimmunotherapy in resectable non-small cell lung cancer: a narrative review

Background and Objective

Neoadjuvant chemoimmunotherapy (NACI) is the standard of care for patients with resectable non-small cell lung cancer (NSCLC). Although the pathological complete response (pCR) after NACI reportedly exceeds 20%, an optimal predictor of pCR is yet to be established. This review aims to examine the possible predictors of pCR after NACI.

Methods

We identified research article published between 2018 and 2022 in English by the PubMed database. Fifty research studies were considered as relevant article, and were examined to edit information for this narrative review.

Key Content and Findings

Recently, several studies have explored potential biomarkers for the pathological response after NACI. For example, 18F-fluorodeoxyglucose positron emission tomography (18F-FDG-PET) imaging, tumor microenvironment (TME), genetic alternation such as circulating tumor DNA (ctDNA), and clinical markers such as neutrophil-to-lymphocyte ratio (NLR) and smoking signature were assessed in patients with resectable NSCLC to predict the pathological response after NACI. Based on the PET response criteria, the complete metabolic response (CMR) achieved a positive predictive value (PPV) of 71.4% for predicting pCR, and the decreasing rate of post-therapy maximum standardized uptake value (SUVmax) after NACI substantially correlated with the major pathological response (MPR). TME, as a significant marker for MPR in tumor specimens, was identified as an increase in CD8+ T cells and decrease in CD3+ T cells or Foxp3 T cells. Considering blood samples, TME comprised an increase in CD4+PD-1+ cells or natural killer cells and a decrease in CD3+CD56+CTLA4+ cells, total T cells, Th cells, myeloid-derived suppressor cells (MDSCs), or regulatory T cells. Although low pretreatment levels of ctDNA and undetectable ctDNA levels after NACI were markedly associated with survival, the relationship between ctDNA levels and pCR remains elusive. Moreover, the patients with a high baseline NLR had a low incidence of pCR. Heavy smoking (>40 pack-years) was favorable for predicting pathological response.

Conclusions

A reduced rate of 18F-FDG uptake post-NACI and TME-related surface markers on lymphocytes could be optimal predictors for pCR. However, the role of these pCR predictors for NACI remains poorly validated, warranting further investigations. This review focuses on predictive biomarkers for pathological response after NACI in patients with resectable NSCLC.

Combining Classic and Novel Neutrophil-Related Biomarkers to Identify Non-Small-Cell Lung Cancer

BACKGROUND

Recent studies have revealed that neutrophils play a crucial role in cancer progression. This study aimed to explore the diagnostic value of neutrophil-related biomarkers for non-small-cell lung cancer (NSCLC).

METHODS

We initially assessed the associations between classic neutrophil-related biomarkers (neutrophil-to-lymphocyte ratio (NLR), absolute neutrophil counts (NEU), absolute lymphocyte counts (LYM)) and NSCLC in 3942 cases and 6791 controls. Then, we measured 11 novel neutrophil-related biomarkers via Luminex Assays in 132 cases and 66 controls, individually matching on sex and age (±5 years), and evaluated their associations with NSCLC risk. We also developed the predictive models by sequentially adding variables of interest and assessed model improvement.

RESULTS

Interleukin-6 (IL-6) (odds ratio (OR) = 10.687, 95% confidence interval (CI): 3.875, 29.473) and Interleukin 1 Receptor Antagonist (IL-1RA) (OR = 8.113, 95% CI: 3.182, 20.689) shows strong associations with NSCLC risk after adjusting for body mass index, smoking status, NLR, and carcinoembryonic antigen. Adding the two identified biomarkers to the predictive model significantly elevated the model performance from an area under the receiver operating characteristic curve of 0.716 to 0.851 with a net reclassification improvement of 97.73%.

CONCLUSIONS

IL-6 and IL-1RA were recognized as independent risk factors for NSCLC, improving the predictive performance of the model in identifying disease.