Lung cancer has high mortality rates globally, with inflammatory processes playing a pivotal role in NSCLC progression. Peripheral blood inflammation markers offer promise for NSCLC risk assessment and prediction.

A retrospective case-control study included 50 NSCLC patients and 50 healthy individuals admitted for routine health examinations as controls. Clinical data were collected, and blood routine tests were conducted on the first day of admission. We compared white blood cells, neutrophils, lymphocytes, monocytes, platelets, NLR (Neutrophil-to-Lymphocyte Ratio), LMR (Lymphocyte-to-Monocyte Ratio), PLR (Platelet-to-Lymphocyte Ratio), dNLR (derived NLR), and SII (Systemic Immune-inflammation Index). Logistic regression and ROC curve analysis were used to evaluate their predictive value.

NLR was significantly higher in NSCLC patients than in healthy controls, and elevated NLR was strongly associated with increased odds of having NSCLC. Neutrophil, lymphocyte, and monocyte counts also contributed to the odds of having NSCLC. NLR showed the highest predictive value with an AUC of 0.911, indicating excellent accuracy.increased odds of having NSCLC.

Our findings suggest that peripheral blood inflammation markers, particularly the NLR, may have potential utility in risk assessment and prediction for NSCLC. These markers warrant further investigation to explore their potential role in early diagnosis and monitoring of NSCLC.

Currently, chemotherapy drugs are the first-line treatment for lung cancer patients, and evaluating their efficacy is of utmost significance. However, assessing the clinical efficacy of chemotherapy drugs remains a challenging task. In recent years, machine learning, especially artificial intelligence (AI), has emerged as a transformative tool in the field of oncology, capable of integrating multiple clinical and protein biomarkers for more accurate predictions. The study collected clinical data and hematological parameters from 2115 lung cancer patients at Hubei Cancer Hospital. Ten typical machine learning models were selected to predict overall survival and progression-free survival, including Decision Tree, Random Forest, Logistic Regression, k-Nearest Neighbors, AdaBoost, XGBoost, and CatBoost. The study found that the CatBoost model performed best in predicting 3-year overall survival and progression-free survival, with AUCs of 0.97 (0.95-0.99) or 0.95 (0.92-0.98). Additionally, the study further analyzed the performance of different machine learning models in patient mortality risk stratification. The CatBoost model excelled in distinguishing between high-risk and low-risk patients, which demonstrated outstanding performance in survival rate prediction at various time points, particularly in predicting survival rates at 1 year (0.54, 0.68), 3 years (0.05, 0.27), and 5 years (0.01, 0.07). The results showed that these models performed well in distinguishing high-risk from low-risk patients, especially the CatBoost model. Therefore, we suggest that these models, particularly the CatBoost model, could serve as practical clinical prediction tools to assist clinicians in developing better and more reasonable treatment plans.

Elevated pre-treatment inflammatory markers predict disease progression and overall survival among adults with renal tumors, including elevated neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR). We hypothesized that elevated inflammatory markers at diagnosis predict higher disease stages and adverse outcomes for children with Wilms tumor.

We performed a retrospective review of children with Wilms tumor who underwent surgical resection at two centers from 2002 to 2022. Differences in patient demographics and laboratory parameters were compared between the overall disease stages. Differences in tumor characteristics and patient outcomes were compared by elevated LMR, NLR, and PLR at diagnosis using Wilcoxon tests and chi-squared or Fisher's exact tests. For LMR, NLR, and PLR, optimal cut points for predicting disease ≥ stage 3 were determined using the Youden index for optimization.

Data were collected from 235 children with Wilms tumor. The median age was 39.8 months and 50.2% of patients were female; 40 had stage 1 disease, 50 had stage 2 disease, 61 had stage 3 disease, 54 had stage 4 disease, and 26 had stage 5 disease. Preoperative inflammatory markers varied with the overall stage. LMR, NLR, and PLR increased as the stage increased. After controlling for age, final histology, and any abnormal genetic marker, elevated NLR, PLR, and LMR at presentation were each associated with significantly higher odds of stage 3 or 4 disease.

Elevation in serum inflammatory markers at diagnosis among children with Wilms tumors is associated with higher disease stage, cancer recurrence, and unfavorable histology.

Platelets play a critical role in tumor immunity, particularly in promoting cancer progression. Numerous studies suggest that platelets could serve as a novel target for cancer immunotherapy, however, no comprehensive reviews have yet summarized and discussed this potential. Our review provides an in-depth discussion of the roles and mechanisms of platelets within both the immunosuppressive tumor microenvironment and the anti-tumor immune microenvironment. Additionally, we summarize the key therapeutic targets and approaches for clinical translation. This work offers essential insights for reprogramming platelets to shift their function from tumor promotion to tumor suppression, providing a foundation for the development of novel immunotherapeutic strategies and related research.

The second most common malignancy after breast cancer is lung cancer (LC). Small cell lung cancer accounts for 15%, while non-small lung cancer (NSCLC) accounts for 85% of cases. Immunotherapy has improved treatment outcomes in NSCLC. However, the role of systemic inflammation-based prognostic scores in predicting response to treatment is not clear. The meta-analyses aims to evaluate the prognostic/ predictive value of inflammatory biomarkers, including NLR, ALI, PLR, CRP, and mGPS, and their potential associated with overall survival in NSCLC patients receiving immunotherapy as first-line or second-line treatment.

A systematic review and meta-analysis was conducted following the Cochrane Handbook and PRISMA guidelines. Searches were performed in PubMed, Cochrane Library, and Web of Science for studies published until January 1, 2022, using specific keywords related to NSCLC, immunotherapy, inflammatory biomarkers and survival. Meta-analysis was performed using RevMan software, analyzing the hazard ratio (HRs) with a 95% confidence interval (CIs) primarily in relation to overall survival.

Six thirty three records were identified, and 17 articles were included in the meta-analysis. The pooled analysis of NLR, ALI, PLR, CRP, and mGPS was significantly associated with OS without significant heterogeneity (NLR: HR = 2.15; 95% CI 1.60 - 2.87; P-Value < 0.00001); (ALI: HR = 2.03; 95% CI 1.43 - 2.88; P-Value < 0.0001); (PLR: HR = 4.06; 95% CI 2.14 - 7.67; P-Value < 0.0001); (CRP: HR = 5.37; 95% CI 3.90 - 7.39; P-Value < 0.00001); and (mGPS: HR = 3.27; 95% CI 1.26 - 8.28; P-Value = 0.01), respectively.

Systemic inflammatory biomarkers demonstrate independent prognostic/ predictive value in patients with advanced non-small cell lung cancer who receive immunotherapy as either the first-line or second-line therapy.

Non-invasive diagnostic monitoring techniques have become essential for treating lung cancer (LC), which continues to be the primary cause of cancer-related death worldwide. The new diagnostic biomarkers called tumour-educated platelets (TEPs) show strong prospects for providing vital information about tumor biology, tumor spread pathways, and treatment reaction patterns. Despite lacking a nucleus, platelets exhibit an active RNA profile that develops through interactions with tumor-derived compounds and the tumor microenvironments (TME). This review explains platelet-tumour interaction regulatory mechanisms while focusing on platelet contributions toward cancer development, immune system avoidance, and blood clot formation. The detection and classification of LC show promise through the analysis of RNA molecules extracted from platelets that encompass mRNAs and non-coding RNAs. RNA sequencing technology based on TEP demonstrates excellent diagnostic power by correctly identifying LC patients alongside their oncogenic alterations of EGFR, KRAS, and ALK. Treatment predictions have proven successful using platelet RNA profiles, specifically in immunotherapy and targeted therapy. Integrating next-generation sequencing with machine learning and artificial intelligence enhances TEP-based diagnostic tools, improving detection accuracy. Standardizing platelet extraction methods and vesicle purification from tumor material needs better development for effective and affordable clinical use. Future investigations should combine TEPs with circulating tumor DNA and exosomal RNA markers to enhance both earliest-stage LC diagnosis and patient-specific therapeutic approaches. TEPs introduce a groundbreaking technique in oncology since they can transform non-invasive medical diagnostics and therapeutic monitoring for cancer.

Aims/Background The resolution of non-tuberculous mycobacterial (NTM) lung disease is associated with the extent of pulmonary lesions and the presence of lung cavities. This study aims to identify factors influencing the development of extensive lung lesions and cavities in patients with NTM lung disease, thereby generating valuable insights for the management and treatment of NTM lung disease. Methods Retrospective analysis was conducted on clinical data from 198 hospitalized patients with NTM lung disease at the Department of Tuberculosis, The Second Hospital of Nanjing, between 2022 and 2023. Patient data like age, gender, past medical history, nutritional risk screening 2002 (NRS-2002) score, lymphocyte count, peripheral blood neutrophil-to-lymphocyte ratio (NLR), pulmonary computed tomography (CT) imaging findings (including extent of lung lesions and presence of cavities), and T cell subsets count were gathered through electronic medical records and hospital information system (HIS) system. Univariate and multivariate logistic regression analyses were carried out with extensive lung lesions and cavities as dependent variables and other factors as independent variables. Results Among the 198 patients, 138 (69.7%) exhibited extensive lung lesions, while cavities were observed in 76 individuals (38.4%). Based on the results of logistic regression analysis, a high NLR (OR = 4.685 [1.176-18.663], p = 0.029) and an NRS-2002 score ≥3 (OR = 12.082 [3.726-39.183], p < 0.001) were identified as risk factors for the development of extensive lung lesions in patients with NTM lung disease. Furthermore, elevated NLR (OR = 3.454 [1.483-8.047], p = 0.004) was associated with an increased risk of cavities in patients with NTM lung disease. Conclusion In patients with NTM lung disease, high NLR is the risk factor for extensive lung lesions and formation of pulmonary cavities, whereas malnutrition elevates the risk for prevalent lung lesions. Early intervention and active monitoring of these related indicators are necessary to prevent disease progression and enhance overall cure rates.

Programmed cell death-ligand 1 (PD-L1) expression is used in treatment decision-making for patients with advanced non-small cell lung cancer, determining if immune checkpoint inhibitors (ICI) are recommended. Patient selection for ICI treatment can be improved by incorporating the host response. We developed and carried out multiple independent validations of a blood-based test designed to stratify outcomes for patients treated with atezolizumab.

A mass spectrometry-based test was developed from a cohort of patients treated with atezolizumab and validated in two clinical trials (n=269, 823) comparing atezolizumab with docetaxel. The test classifies patients as Good or Poor indicating better or worse outcomes, respectively. The prognostic and predictive power of the test was assessed and evaluated within PD-L1 subgroups. Protein enrichment methods were used to investigate the association of test classification with biological processes.

Approximately 50% of patients were assigned to each classification in all three cohorts. When treated with atezolizumab, the Good subgroup had superior outcomes in all cohorts. Overall survival (OS) HR (95% CI) for Good patients in each cohort was: 0.23 (0.12 to 0.44), 0.32 (0.21 to 0.51), and 0.52 (0.41 to 0.66) and persisted in all PD-L1 subgroups. The test was predictive of differential OS and progression-free survival in one cohort, but not in the other. Enrichment techniques indicated the test was associated with acute inflammatory response, acute phase response, and complement activation.

Aspects of host immune response to disease can be assessed from the circulating proteome and provide outcome stratification for patients treated with atezolizumab. Combining this information with PD-L1 measurements improves prediction of outcomes.

This study evaluates the impact of thoracic radiotherapy (TRT) combined with immune checkpoint inhibitors (ICIs) treatment-related pneumonitis on tumor progression and prognosis in patients with non-small cell lung cancer (NSCLC).

Data were collected retrospectively from NSCLC patients treated with TRT and ICIs between January 2019 and August 2023. Treatment-related pneumonitis (TRP) was assessed and graded using the Common Terminology Criteria for Adverse Events (CTCAE) and the Chinese Society of Clinical Oncology Guidelines for Managing Immunotherapy-Related Toxicities. Kaplan-Meier curves and log-rank tests examined associations between pneumonitis with local recurrence-free survival (LRFS), distant metastasis-free survival (DMFS), progression-free survival (PFS), and overall survival (OS). COX regression identified prognostic factors in the pneumonitis group.

Among 86 patients, 58 (67.4%) developed TRP, including 37.2% with grade 2 pneumonitis, and no grade ≥3 cases. 12 patients (14.0%) developed mixed radiation and ICIs pneumonitis. The pneumonitis group had significantly shorter DMFS (12.07 vs not reached, p = 0.028) and PFS (9.53 vs 14.27 months, p = 0.040), shorter LRFS compared to the non-pneumonitis group, but similar OS. High-grade pneumonitis correlated with worse outcomes, especially DMFS (p = 0.031), basically no differences among pneumonitis types. Multivariate COX analysis identified solitary pulmonary nodules or masses as independent negative prognostic factors for PFS, while higher MLD (mean lung dose) independently predicted reduced OS.

Pneumonitis resulting from TRT combined with ICIs was associated with shorter PFS but did not affect OS in NSCLC patients. Mixed pneumonitis did not worsen outcomes. Larger prospective studies are needed to validate these findings.

The utility of the immune prognostic index (IPI) for esophageal squamous cell carcinoma (ESCC) has yet to be established after minimally invasive esophagectomy (MIE). The purpose of this study was to investigate the value of IPI in predicting the prognosis and postoperative adjuvant chemotherapy (AC) benefits of ESCC patients.

Between January 2011 and December 2018, 613 ESCC patients underwent MIE at our center and were divided into two groups: low IPI and high IPI.Log-rank tests were used to compare the overall survival (OS) and disease-free survival (DFS) of patients in different groups based on Kaplan-Meier survival analysis. Differences in clinical characteristics between groups were eliminated by propensity score matching (PSM) analysis. To identify independent risk factors influencing OS and DFS, the Cox proportional risk model was used.

In comparison to the high IPI group, the low IPI group had a better 5-year OS and DFS in both the entire and matched cohorts (P < 0.05). IPI was found to be an independent prognostic factor for OS and DFS in a multivariate analysis of the entire cohort and the matched cohort (P < 0.05). In subgroup analyses of most clinicopathological factors, high IPI was associated with a higher risk of death or recurrence in the matched cohorts. When combined with 8th TNM staging, the 5-year OS and DFS of stage II or III patients with low IPI in the AC group were not different from those in the non-AC group (P > 0.05), and AC of stage III patients with high IPI significantly prolonged 5-year OS and DFS (OS: 37.4% vs 26.2%, P = 0.018; DFS: 33.6% vs 19.8%, P = 0.042).

Preoperative IPI is a promising predictor of ESCC after MIE. For stage III ESCC patients with high IPI, AC can significantly reduce the risk of death or recurrence.

It has been proposed that more aggressive tumors trigger a stronger inflammatory response than less aggressive types. We hypothesize that systemic immune-inflammatory index (SII) is associated with occult nodal disease (OND) in clinically node-negative patients undergoing lung resection for non-small cell lung cancer (NSCLC).

The study included patients who underwent lung resection with nodal dissection, according to current guidelines, at a single center between 2010 and 2021 for NSCLC. Preoperative SII within 3 weeks of surgery was calculated. OND was defined as a clinically node-negative patient found to be pathologically node-positive. Cut-point analysis for SII was performed to identify the level most strongly associated with OND. Univariable and multivariable logistic regressions were used to examine the association between SII, clinical factors, and OND.

A total of 199 patients met inclusion criteria, of whom 51% (102 of 199) were women. The median number of nodes and nodal stations examined was 13 (interquartile range 9 to 17) and 6 (interquartile range 5 to 6), respectively. The cut point was determined to be SII 112 or more. On univariable analysis, high SII was associated with OND (odds ratio 15.75, 95% CI 2.09 to 118.73, p = 0.007). On multivariable analysis, after controlling for age, BMI, approach, sex, smoking history (pack-years), forced expiratory volume in 1 second, performance status, comorbidity, histology, lymphovascular invasion, tumor differentiation, and tumor size, high SII was associated with OND (odds ratio 34.59, 95% CI 2.69 to 444.88, p = 0.007).

Increased SII is associated with OND in patients undergoing lung resection for NSCLC.

To investigate the relationship between platelet-to-lymphocyte ratio (PLR) or neutrophil-to-lymphocyte ratio (NLR) and Immune checkpoint inhibitor (ICI)-induced thyroid dysfunction.

This was a single-center retrospective observational study of patients with solid tumors receiving ICI therapy. Clinical characteristics of patients were assessed at baseline and during ICI therapy. Logistic regression was implemented to assess the association of PLR and NLR with thyroid dysfunction. Kaplan-Meier method was used to analyze the difference in time between the onset of hypothyroidism and thyrotoxicosis.

A total of 355 patients with solid tumors were included in our study. Sixty-nine (19.44%) patients developed ICI-induced thyroid dysfunction after receiving ICI therapy, with a median (IQR) time to onset of 91(34-203.5) days. Patients with high PLR (H-PLR) had an increased risk of ICI-induced thyroid dysfunction (OR = 1.87, 95% CI 1.07-3.28, P = 0.028) compared to those with low PLR (L-PLR). Specifically, H-PLR was associated with ICI-induced thyrotoxicosis but not hypothyroidism (OR = 2.40, 95% CI 1.09-5.29, P = 0.030). Meanwhile, NLR was not correlated with ICI-induced thyroid dysfunction as a continuous (P = 0.699) or categorical variable (P = 0.914). The sensitivity analysis showed that H-PLR remains positively correlated with ICI-induced thyroid dysfunction.

PLR rather than NLR was associated with the occurrence of ICI-induced thyroid dysfunction. Furthermore, PLR may serve as a predictive biomarker for ICI-induced thyroid dysfunction.

Immune checkpoint inhibitors have revolutionized the management of advanced non-small cell lung cancer (NSCLC). While the proportion of "long-term survivors" is estimated to be between 8% and 16%, this population remains poorly understood.

BREATH is a retrospective observational study including patients with metastatic or non-radically treatable locally advanced NSCLC, treated with immunotherapy and presenting with controlled disease for at least 12 months after the first immunotherapy injection. The main objective is to describe the characteristics of this population.

Forty-nine patients were included in the study. After a median follow-up of 51 months, median progression-free survival (PFS) or overall survival (OS) was not reached. At 36 months, PFS was 64.7% and OS was 91.6%. Patients who received a complete immunotherapy regimen (two years) had a higher rate of PFS (HR 0.046; 95% CI [0.14-0.98]; P=0.03) than those who received an incomplete regimen. An albumin level≥35g/L at the start of immunotherapy was the only factor associated in multivariate analysis with prolonged PFS.

Patients with advanced NSCLC and prolonged disease control under immunotherapy exhibit exceptionally long survival, pointing to a possible paradigm shift in our practices.

Immune checkpoint inhibitors (ICIs) offer durable progression-free survival (PFS) benefit in a subset of patients with advanced non-small cell lung cancer (NSCLC). However, the predictors of long-term PFS (LTPFS) remain unclear.

Advanced NSCLC patients receiving first-line ICIs monotherapy at Guangdong Lung Cancer Institute between December 2017 and August 2022 were identified. Predictive value of different characteristics was evaluated in LTPFS (PFS ≥ 24 months) compared with short-term PFS (STPFS, PFS ≤ 3 months). Circulating cytokine levels were evaluated in paired peripheral blood samples collected before and after ICIs treatment.

Among 202 patients identified and 171 included (median follow-up: 41.0 months), 44 (25.7%) experienced LTPFS, associated with a 5-year overall survival (OS) rate of 81.2%. Squamous NSCLC, intermediate or poor lung immune prognostic index (LIPI) score, and liver metastases, were negatively associated with LTPFS. High tumor mutational burden (TMB, ≥ 10 mutations/megabase) was enriched in LTPFS compared to STPFS (P = 0.002). Patients with both high TMB and PD-L1 demonstrated the greatest survival benefit from first-line ICIs monotherapy (median PFS: 24.5 months, median OS: 67.0 months). Thirty-eight peripheral blood samples were collected before and after ICIs treatment from 10 patients with LTPFS and 9 with STPFS, which revealed increased CCL11 (P = 0.013) and decreased IL1RA (P = 0.001) and IL17A (P = 0.003) levels in LTPFS after ICIs treatment.

Distinct clinical characteristics, including TMB, PD-L1, pathologic subtypes, LIPI score, number of organs involved, metastatic sites, and dynamic circulating cytokines profile features, can distinguish NSCLC patients achieving LTPFS from those with STPFS following first-line ICIs monotherapy.

Older patients with lung cancer are underrepresented in pivotal trials of immune checkpoint inhibitors (ICIs). This study primarily retrospectively evaluated the older patients with lung cancer treated with ICIs to determine which factors are related to the occurrence and prognosis of ICI-related pneumonitis (CIP).

We conducted a single-center, retrospective study of patients age ≥ 65 years diagnosed with lung cancer who received ICIs between January 2018 and June 2023 at the First Hospital of China Medical University. Clinical characteristics and blood parameters at baseline (before ICIs), at onset of pneumonitis (in the CIP group), and before the last dose of ICIs (in the non-CIP group) were collected and compared.

A total of 205 older patients with lung cancer were included, of which 51 (24%) patients developed CIP. Radiotherapy history, first line treatment, and the increased baseline systemic immune-inflammation index (SII), and CD4/CD8 were significantly and independently associated with the risk of CIP. Significant increase in CRP and decrease in albumin (ALB), prognostic nutritional index (PNI), and PaO2 were observed from baseline to CIP during treatment with ICIs. The PD-L1 expression status < 50% (P = 0.022) was the risk factor affecting their progression free survival (PFS). ECOG PS ≥ 2 (P = 0.031) and high-CRP (P = 0.007) of older patients were significantly correlated with their overall survival (OS), and patients who experienced CIP had a better OS than non-CIP (P = 0.001). The older patients with interstitial lung abnormalities (ILA) showed a shorter PFS than those without ILA (P = 0.036), and the PD-L1 expression status < 50% (P = 0.005), and low ALB (P = 0.023) was correlated with the OS in CIP.

Radiotherapy history, first line treatment (mostly in combination therapy), and increased baseline SII and CD4/CD8 were associated with the occurrence of CIP in older patients with lung cancer. PD-L1 expression status < 50%, ECOG PS ≥ 2 and high-CRP were associated with worse prognosis in all older patients. ILA, PD-L1 expression status < 50% and low-ALB at onset of CIP were related to poor prognosis in CIP.

Immune checkpoint inhibitor (ICI) plus chemotherapy has become the standard of care for advanced non-small cell lung cancer (NSCLC). Nonetheless, reliable efficacy biomarkers of ICI plus chemotherapy are lacking. In this research, we sought to explore efficacy biomarkers and construct robust prognostic models in NSCLC patients treated with ICI plus chemotherapy.

We retrospectively analyzed 171 patients with advanced NSCLC treated with ICI plus chemotherapy. Clinical characteristics and peripheral blood inflammatory indexes were collected and prognostic models were constructed to explore efficacy and prognosis biomarkers of ICI plus chemotherapy.

In the cohort that received first-line ICI plus chemotherapy, pre-treatment neutrophil-to-lymphocyte ratio (NLR) > 3.3 and fibrinogen (FIB) > 3.196 were associated with worse efficacy and were independent risk factors of progression-free survival (PFS). Compared to programmed cell death ligand 1 (PD-L1), the derived NLR-FIB (NF) score had significantly improved accuracy in predicting efficacy and prognosis. In advanced NSCLC patients with targetable oncogenic driver alterations receiving second- or post-line ICI plus chemotherapy, pre-treatment NLR > 3.53 was associated with worse efficacy and was an independent risk factor of PFS and OS; Tyrosine kinase inhibitor (TKI)-PFS > 12 months were independent risk factors of overall survival (OS). Secondary epidermal growth factor receptor (EGFR)-T790M mutation, platelet-to-lymphocyte ratio (PLR) > 196.81 and albumin (ALB) < 40.25 were associated with worse PFS. Based on NLR and TKI-PFS, an NLR-TKI-PFS (NTP) score was constructed with three OS risk prognosis categories: favorable, intermediate, and poor (corresponding to a median OS of 21, 12, and 5.3 months).

The noninvasive NF score, combining NLR > 3.3 and FIB > 3.196, was superior to PD-L1 estimated from tumor tissue in predicting the efficacy and prognosis of first-line ICI plus chemotherapy in advanced NSCLC patients. The noninvasive NTP score, combining NLR > 3.53 and TKI-PFS > 12 months, is a valuable tool for predicting OS and PFS in advanced NSCLC patients with targetable oncogenic driver alterations receiving second- or post-line ICI combination therapy.

Peripheral complete blood cell count (CBC) and blood ratios, including neutrophil-to-lymphocyte ratio (NLR), neutrophil-to-red blood cell ratio (NRR), and platelet-to-lymphocyte ratio (PLR), have been used in the diagnosis and prognosis of several cancers; however, their relevance in canine splenic hemangiosarcoma (HSA) remains to be investigated. This study investigated whether CBC, NLR, NRR, and PLR could be diagnostic and prognostic biomarkers in dogs with splenic HSA. Analyzing medical records of 154 dogs undergoing splenectomy from 2018 to 2022, we found that dogs diagnosed with splenic HSA (n = 63) had significantly higher neutrophil counts (14.9 ± 9.7 vs. 12.6 ± 9.6; p < 0.001), increased NRR (3.7 ± 2.6 vs. 2.7 ± 3.7; p < 0.001), lower platelet counts (145 ± 111 vs. 270 ± 213; p < 0.001), and reduced PLR (139.4 ± 160.0 vs. 259.9 ± 278.0; p < 0.001) compared to dogs with other splenic lesions. This study also identified a higher risk of relapse and mortality associated with increased NRR (p < 0.001 and p = 0.012, respectively) and an inverse relationship with PLR (p = 0.015 and p = 0.033, respectively), whereas NLR showed no significant association. The multivariate survival analysis identified NRR as an independent prognostic factor for DFI [hazard ratio (1.837); 95% confidence interval (1.147-2.942); p = 0.011], while for OS, the association did not reach statistical significance [hazard ratio (1.510); 95% confidence interval (0.985-2.314); p = 0.059]. These findings highlight the potential of NRR and PLR as biomarkers for assessing diagnosis and prognosis in canine splenic HSA, advocating for further validation in the future.

This study aimed to identify clinical factors and develop a predictive model for pathological complete response (pCR) and major pathological response (MPR) in non-small cell lung cancer (NSCLC) patients receiving neoadjuvant chemotherapy combined with immune checkpoint inhibitors (ICIs).

Cases meeting inclusion criteria were divided into high- and low-risk groups according to 75 clinical indicators based on tenfold LASSO selection. Logistic regression was employed to analyze both pCR and MPR. The accuracy of the nomograms was assessed using the time-dependent area under the curve (AUC).

A total of 297 patients from four multiple centers were included in the study, with 212 assigned to the training set and 85 to the testing set. The AUC was determined for the prediction of pCR (training: 0.97; testing: 0.88) and MPR (training: 0.98; testing: 0.81). Significant associations were observed between the preoperative tumor maximum diameter, preoperative tumor maximum standardized uptake value (SUVmax), changes in tumor SUVmax, percentage of tumor reduction, baseline total prostate-specific antigen (TPSA) and pathological response (P < 0.001).

The combined application of clinical indicators including non-invasive tumor imaging and hematology can help clinicians to obtain a higher ability to predict NSCLC patient's pathological remission, and the effect is better than that of clinical factors alone. These findings could help guide personalized treatment strategies in this patient population.

Anti-programmed cell death-1 (anti-PD-1) therapy has become the standard immunotherapy for patients with advanced non-small cell lung cancer (NSCLC). However, little is known about the organs influenced by PD-1 inhibitors on a patient's tumor immunity. We examined the changes in lymphoid tissue proliferation before and after PD-1 inhibitor treatment using 3'-deoxy-3'-[18F]-fluorothymidine (18F-FLT) positron emission tomography (PET). This study included 25 patients with advanced NSCLC who underwent 18F-FLT PET before and 2 and 6 weeks after the initiation of PD-1 inhibitor treatment. We determined the average standardized uptake value (SUVmean) in the spleen, maximum SUV (SUVmax) in the lymph nodes, and the SUVmax, SUVmean, proliferative vertebral volume (PVV), and total vertebral proliferation (TVP) in the thoracolumbar vertebral bodies using 18F-FLT PET and blood test data. The relationship between the rate of change in these parameters before and after treatment and the tumor response was evaluated.

The baseline 18F-FLT accumulation in the lymphoid tissues or blood test data between the progressive disease (PD) and non-PD groups were not significantly different. In the spleen and lymph nodes, changes in 18F-FLT accumulation from baseline to 2 or 6 weeks did not differ between the non-PD and PD groups. However, mediastinal lymph node accumulation tended to increase transiently at week 2 compared to that before treatment initiation (median SUVmax 2.19 vs. 2.64, P = 0.073). Regarding changes in vertebral accumulation in the non-PD group, the SUVmax, and PVV were significantly lower at weeks 2 and 6. In the percent changes in 18F-FLT accumulation of the vertebrae after the treatment initiation, the PD group was significantly higher than the non-PD group at the 6-week evaluation (median ΔTVP0-6, 17.0% vs. -13.0%, P = 0.0080).

In patients with advanced NSCLC who achieved a tumor response, proliferation decreased in the bone marrow, but not in the spleen or lymph nodes, 6 weeks after treatment initiation. 18F-FLT PET can help monitor changes in tumor immunity in each lymphoid tissue and may serve as a biomarker for the response to immune checkpoint inhibitor therapy.

Accumulating research has implicated that vitamin D (VD) may be important in the pathogenesis of Crohn's disease (CD), while the platelet-to-lymphocyte ratio (PLR) is emerging as a biomarker in immune disorders. However, the synergistic effect of VD and PLR on treatment escalation in newly diagnosed CD patients remains unclear. Therefore, this study aims to assess the interaction between PLR and VD on the subsequent use of infliximab and/or immunosuppressants in patients with CD.

Newly diagnosed CD patients were selected from the Sir Run Run Shaw Hospital Inflammatory Bowel Disease Biobank (SRRSH-IBC). COX proportional hazards models were employed to assess the association between VD, PLR, and treatment escalation among CD patients.

Among 108 newly diagnosed CD adult patients, vitamin D deficiency (VDD) was prevalent (78.7%). Compared to CD patients without VDD, those with VDD exhibited a higher risk of treatment escalation, i.e., using infliximab and/or immunosuppressants (HR = 3.22, 95% CI = 1.24-8.35, P = 0.016). There is a clear trend of decreasing risk of treatment escalation as VD levels elevating (HR = 0.26, 95% CI = 0.09-0.76, P for trend = 0.014). The stratified analysis revealed a noteworthy interaction between PLR and VD levels concerning treatment escalation. Baseline VDD amplified the risk of treatment escalation among patients with elevated PLR (HR = 4.17, 95% CI = 1.51-11.53, Pinteraction = 0.031). Similar trends were observed when VD levels were stratified into quartiles (highest quartile vs. lowest quartile: HR = 0.18, 95% CI = 0.05-0.62, P for trend = 0.014).

This study underscores a significant interplay between VD levels and PLR in influencing treatment outcomes in CD. VDD exacerbates the risk of treatment escalation primarily in individuals with heightened PLR levels, highlighting the combined impact of vitamin D status and inflammation on disease progression of CD.

The nursing science precision health (NSPH) model considers identifying the biological basis of symptoms in order to develop precise intervention strategies that ultimately improve the overall health of the symptomatic individual. This study sought to construct a nomogram for predicting cancer-related cognitive impairment (CRCI) in patients with lung cancer within the context of the NSPH model.

A cohort of 252 patients with lung cancer was prospectively collected and randomly divided into training and validation cohorts in a 7:3 ratio. The least absolute shrinkage and selection operator (LASSO) regression method optimized variable selection, followed by multivariate logistic regression to develop a model, which subsequently formed the basis for the nomogram. The nomogram's discrimination and calibration were evaluated using a calibration plot, the Hosmer-Lemeshow test, and the receiver operating characteristic curve (ROC). Decision curve analysis (DCA) quantified the net benefits of the nomogram across various threshold probabilities.

Five pivotal variables were incorporated into the nomogram: age (≥ 65 years), treatment, education level, albumin, and platelet-to-lymphocyte ratio (PLR). The area under the ROC curve (0.970 for the training cohort and 0.973 for the validation cohort) demonstrated the nomogram's excellent discriminative ability. Calibration curves closely aligning with ideal curves indicated accurate predictive capability. Moreover, the nomogram exhibited a positive net benefit for predicted probability thresholds ranging from 1 to 98% in DCA.

Key risk factors, including advanced age (≥ 65 years), low education level, combined chemotherapy, low albumin, and high PLR, were significantly associated with higher CRCI incidence. This nomogram model has good performance and can help identify CRCI with high accuracy in lung cancer patients.

The therapeutic landscape of locally advanced or metastatic urothelial carcinoma (mUC) is rapidly evolving, and immune checkpoint inhibitors (ICI) have become an integral part of the standard therapy. However, the majority of patients do not benefit from this treatment. Hence, finding prognostic and predictive biomarkers may improve therapeutic decision-making. The aim of this study was to analyze the prognostic and predictive significance of liquid biomarkers (NLR, CRP, PLR, and LDH) in mUC patients treated with ICI.

We collected articles from PubMed, Cochrane, and Embase databases with primary outcomes of overall survival (OS), progression-free survival (PFS) and objective response rate (ORR).

We compiled data from a total of 6,673 ICI-treated patients with locally advanced or mUC from 31 articles. Pooled univariate analysis demonstrated that high pre-treatment NLR is significantly associated with worse OS (HR: 2.19; 95% CI: 1.80-2.68) and PFS (HR: 1.90; 95% CI: 1.57-2.31). Similarly, elevated CRP levels were associated with worse OS (HR: 1.75; 95% CI: 1.37-2.24) and PFS (HR: 1.58; 95% CI: 1.26-1.99).

Elevated pre-treatment NLR, CRP, PLR, and LDH are significantly associated with worse OS and PFS in ICI-treated urothelial carcinoma patients, suggesting that they have potential prognostic and predictive value in treatment decisions.

In this systematic review and meta-analysis we summarized the existing data on inflammatory laboratory biomarkers and their potential impact on immunotherapy outcomes in urothelial cancers.

https://www.crd.york.ac.uk/prospero/, identifier CRD42022291449.

To predict the incidence of immune-related Adverse Events (irAEs) in patients with recurrent or metastatic Nasopharyngeal Carcinoma (NPC) treated with Programmed Death-Ligand 1 (PD-L1) inhibitors, this study developed and validated nomogram models incorporating demographic, clinical, and biological variables.

Data from 153 NPC patients were analyzed, incorporating variables including age, sex, Body Mass Index (BMI), clinical stage, and biomarkers. Predictive models were constructed using multivariable logistic regression, Least Absolute Shrinkage and Selection Operator (LASSO) regression, and Ridge regression. The models' performance was evaluated using Receiver Operating Characteristic (ROC) curves, calibration curves, and Decision Curve Analysis (DCA). Internal validation was conducted through k-fold cross-validation.

Independent predictors of irAEs included PD-L1, Free Thyroxine (FT4), Sodium (Na), and lymphocyte counts. Of the three models, the stepwise regression model performed best, with an area under the curve (AUC) of 0.78. Calibration curves showed a strong correlation between predicted and observed outcomes, and DCA demonstrated high clinical utility.

The nomogram models effectively predict irAEs in NPC patients treated with PD-L1 inhibitors. Early identification of patients with elevated PD-L1, abnormal FT4, Na, or irregular lymphocyte counts allows for closer monitoring and personalized treatment, potentially improving outcomes. Further research is required to confirm these findings across other cancer types and therapies.

Systemic nutrition and inflammation status is recognized for its influence on cancer survival, yet its role in perioperative outcomes remains poorly defined. This study aimed to refine the assessment of systemic nutrition and inflammation status in non-small cell lung cancer (NSCLC) patients and to elucidate its impact on perioperative outcomes.

All patients underwent video-assisted thoracoscopic lobectomy, with their nutrition and inflammation status assessed based on preoperative blood tests. The development cohort, comprising 1497 NSCLC patients from two centers, evaluated the predictive value of systemic nutrition/inflammation indicators for perioperative endpoints and formulated the systemic nutrition-inflammation index (SNII). The tertiles of SNII were used to classify the nutrition/inflammation risk as high (< 15.6), moderate (15.6-23.1), and low (> 23.1). An external validation cohort of 505 NSCLC patients was utilized to confirm the effectiveness of SNII in guiding perioperative management.

In the development cohort, the SNII tool, calculated as the product of total cholesterol and total lymphocytes divided by total monocytes, demonstrated a stronger correlation with perioperative outcomes compared to 11 existing nutrition/inflammation indicators. A low SNII score, indicative of high nutrition/inflammation risk, was independently predictive of increased complication incidence and severity, as well as prolonged chest tube duration and hospital stay. These findings were corroborated in the validation cohort. Upon combining the development and validation cohorts, the superiority of the SNII in predicting perioperative outcomes was further confirmed over the existing nutrition/inflammation indicators. Additionally, comprehensive subgroup analyses revealed the moderately variable efficacy of SNII across different patient populations.

This study developed and validated the SNII as a tool for identifying systemic nutrition and inflammation risk, which can enhance perioperative managements in NSCLC patients. Patients identified with high risk may benefit from prehabilitation and intensive treatments, highlighting the need for further research.

Perioperative inflammatory indices reflect systemic inflammatory responses and have been linked to cancer progression and prognosis. This study aims to explore the differences in perioperative inflammatory indices between lung squamous cell carcinoma (LSCC) and adenocarcinoma (LUAD) and their association with long-term outcomes.

This study included 287 lung cancer patients who underwent curative resection between June 2016 and December 2017, comprising 61 cases of LSCC and 226 cases of LUAD. Perioperative baseline information and inflammatory cell counts were collected. Patients were followed up for a median duration of 76 months, during which disease-free survival (DFS) and overall survival (OS) were recorded. Cox regression analysis was used to evaluate the prognostic significance of inflammatory factor levels.

Significant differences were observed in white blood cell count and systemic inflammation response index (SIRI) between LSCC and LUAD (P < 0.05). Regression analysis identified age (OR=2.096, P=0.004), postoperative day 1 D-dimer level (OR=1.550, P<0.001), and Platelet-to-lymphocyte ratio (PLR) (OR=1.901, P=0.031) as independent risk factors for perioperative venous thromboembolism (VTE). Furthermore, open surgical approach (HR=2.437, P=0.016), tumor type (LSCC; HR=2.437, P=0.016), and PLR (HR=1.534, P=0.019) were independent risk factors for DFS.

Inflammatory index is key predictors of perioperative VTE and DFS in lung cancer, emphasizing their critical role in prognosis.

Postoperative pneumonia significantly affects recovery and prognosis in patients with esophageal squamous cell carcinoma. The CALLY index, derived from preoperative hematological parameters, may serve as a predictive marker for such complications.

To assess the association between preoperative inflammatory status via the CALLY index and the occurrence of postoperative pneumonia in patients with resectable ESCC.

A retrospective cohort study was conducted from January 2020 to December 2022 at The Affiliated Huai'an No. 1 People's Hospital of Nanjing Medical University. A total of 215 patients who met inclusion criteria were analyzed. Clinical data, including CALLY indices calculated preoperatively, were collected. Propensity score matching was applied to minimize confounding biases. The predictive value of the CALLY index was assessed using receiver operating characteristic analysis, and logistic regression was used to identify factors associated with postoperative pneumonia.

ROC curve analysis demonstrated the CALLY index had an area under the curve of 0.764 for predicting postoperative pneumonia, with a cutoff value of 1.97 achieving 67.69% sensitivity and 84.67% specificity. In multivariate analysis, a lower CALLY index was significantly associated with increased pneumonia risk, independent of other factors (adjusted OR = 0.66, p < 0.001). High CALLY index scores correlated with a decreased likelihood of postoperative pneumonia, reinforcing its utility as a non-invasive prognostic marker.

The CALLY index is a robust, independent predictor of postoperative pneumonia in patients with resectable ESCC. Preoperative assessment of this index could enhance risk stratification and guide proactive management strategies to improve postoperative outcomes.

Young patients diagnosed with non-small cell lung cancer (NSCLC) present unique clinical, pathological, and genetic features, resulting in a highly heterogeneous patient population. The current TNM staging system is insufficient for accurately predicting their prognosis. This study aims to develop a nomogram model for survival prediction in young patients with metastatic NSCLC at initial diagnosis and further verify the effectiveness of the model.

This study enrolled 961 young patients diagnosed with metastatic NSCLC in the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2017. The patients were allocated into a training cohort (n = 673) and an internal validation cohort (n = 288). An additional 215 patients from the Fourth Hospital of Hebei Medical University were included as a Chinese external validation cohort. Univariate and multivariate Cox regression analyses were conducted in the training cohort to identify independent risk factors influencing survival, which were used to develop a nomogram model. The model's effectiveness was evaluated using C-index, calibration curve, receiver operating characteristic (ROC) curve, decision curve analysis (DCA) curve, and Kaplan-Meier survival curve.

The multifactorial Cox regression model identified eight independent risk factors influencing overall survival (OS): race, marital status, histological type, T stage, N stage, liver metastasis, chemotherapy, and radiotherapy (all P < 0.05). These factors were incorporated into the nomogram, which achieved a C-index of 0.673 [95% confidence interval (CI) = 0.661-0.685]. The nomogram exhibited excellent prognostic value in both internal (C-index = 0.662, 95% CI = 0.643-0.681) and external (C-index = 0.724, 95% CI = 0.702-0.746) validation cohorts. In addition, calibration curves for 0.5-,1-, 2-, 3-, and 5-year OS probabilities showed close agreement between predicted and observed survival outcomes across various time points. Additionally, ROC curve analysis and Kaplan-Meier curves highlighted the robust discriminatory power of the model based on survival outcomes. Moreover, the DCA analysis revealed that the incremental net benefit of this model was significantly superior to that of the TNM staging system alone.

A nomogram model has been developed and validated to accurately predict the OS of young patients with metastatic NSCLC at initial diagnosis, demonstrating superior performance compared to the traditional TNM staging system. This model offers valuable guidance for precise predictions and making rational treatment decisions in clinical practice.

Neutrophil-to-lymphocyte ratio (NLR) can be treated as a simple indicator of patients' immune status by representing the state of the systemic inflammatory response. Immunotherapy now is the accepted second-line treatment for recurrent or metastatic nasopharyngeal carcinoma (R/M NPC). However, the significance of NLR in patients with R/M NPC undergoing treatment with PD-L1 (programmed cell death-ligand 1) inhibitors is still uncertain.

We analyzed the relationship between baseline NLR with 153 patients' efficacy and survival from a multicenter, prospective, Phase 2 study. We employed restricted cubic spline plots to get the nonlinear relationship between NLR and progression-free survival (PFS) or overall survival (OS). We identified the ideal cut-off value through the analysis of the receiver operating characteristic curve (ROC curve). We used Logistic regression, Cox regression, Log-rank test, and Kaplan-Meier method to analyze the association between NLR and patients' disease control rate (DCR) and PFS or OS.

The ideal threshold value for NLR was 2.826. NLR was identified as a significant independent predictor of DCR (OR = 0.17, 95% CI = 0.05-0.48, p = 0.001), indicating that a higher NLR is associated with worse DCR. NLR (AUC = 0.634) showed superior predictive capability for DCR in comparison to lymphocytes (AUC = 0.602) and neutrophils (AUC = 0.593). High NLR values were risk factors both for poor PFS (HR = 2.53, 95% CI = 1.58-4.06, p < 0.001) and OS (HR = 3.89, 95% CI = 2.09-7.24, p < 0.001).

Elevated NLR is strongly associated with lower response to treatment and reduced survival rates in patients with R/M NPC being treated with PD-L1 inhibitors. Patients with high NLR values have poor efficacy and survival.

Pretreatment immune dynamics and nutritional status are important predictors of survival outcomes in various malignancies. This study was performed to evaluate the relationships between survival outcomes and the pretreatment nutritional indices - Onodera's prognostic nutritional index (OPNI) and neutrophil-to-lymphocyte ratio (NLR) - in 42 patients with recurrent or metastatic oral squamous cell carcinoma (OSCC) who underwent treatment with immune checkpoint inhibitors (ICI). Additionally, the relationships between these nutritional indices and T-cell exhaustion in the peripheral blood of the patients were analysed. As a result, the Kaplan-Meier method revealed that lower OPNI was significantly associated with poorer overall survival (OS) and progression-free survival (PFS) (both P < 0.001). Likewise, the results of the multivariate analysis showed that a low OPNI was independently associated with poor 5-year OS (hazard ratio 4.36, P = 0.008) and PFS (hazard ratio 4.04, P = 0.010). Patients with a low OPNI had a significantly higher frequency of PD-1+ CD8+ T-cells than those with a high OPNI (P = 0.009). These findings demonstrate that pretreatment OPNI is a valuable independent prognostic indicator of OS and PFS in OSCC patients following treatment with ICI. The OPNI might reflect T-cell exhaustion in the peripheral blood of OSCC patients.

Patients with early-stage hepatocellular carcinoma (HCC) generally have good survival rates following surgical resection. However, a subset of these patients experience recurrence within five years post-surgery.

To develop predictive models utilizing machine learning (ML) methods to detect early-stage patients at a high risk of mortality.

Eight hundred and eight patients with HCC at Beijing Ditan Hospital were randomly allocated to training and validation cohorts in a 2:1 ratio. Prognostic models were generated using random survival forests and artificial neural networks (ANNs). These ML models were compared with other classic HCC scoring systems. A decision-tree model was established to validate the contribution of immune-inflammatory indicators to the long-term outlook of patients with early-stage HCC.

Immune-inflammatory markers, albumin-bilirubin scores, alpha-fetoprotein, tumor size, and International Normalized Ratio were closely associated with the 5-year survival rates. Among various predictive models, the ANN model generated using these indicators through ML algorithms exhibited superior performance, with a 5-year area under the curve (AUC) of 0.85 (95%CI: 0.82-0.88). In the validation cohort, the 5-year AUC was 0.82 (95%CI: 0.74-0.85). According to the ANN model, patients were classified into high-risk and low-risk groups, with an overall survival hazard ratio of 7.98 (95%CI: 5.85-10.93, P < 0.0001) between the two cohorts.

A non-invasive, cost-effective ML-based model was developed to assist clinicians in identifying high-risk early-stage HCC patients with poor postoperative prognosis following surgical resection.

Ovarian cancer is one of the most lethal gynecological malignancies. This study aimed to evaluate the prognostic significance of complete blood count (CBC) and lipid profile in patients with optimally debulked epithelial ovarian cancer (EOC) and develop a nomogram model to predict recurrence-free survival (RFS).

This retrospective study analyzed patients diagnosed with EOC between January 2018 and June 2022.

A total of 307 patients were randomly divided into training and validation sets in a ratio of 7:3. Grade, International Federation of Gynecology and Obstetrics (FIGO) stage, platelet-to-lymphocyte ratio, red blood cell distribution width-coefficient of variation, triglycerides, and human epididymal protein 4 were identified as independent prognostic factors. The novel nomogram displayed a good predictive performance, with a concordance index (C-index) of 0.787 in the training group and 0.807 in the validation group. The areas under the curve for 1-, 3-, and 5-year RFS were 0.770, 0.881, and 0.904, respectively, in the training group, and 0.667, 0.906, and 0.886, respectively, in the validation group. The calibration curves exhibited good concordance between the predicted survival probabilities and actual observations. Time-dependent C-index curves, integrated discrimination improvement, net reclassification index, and decision curve analysis showed that the nomogram outperformed FIGO staging.

This study established and validated a nomogram combining CBC and lipid profiles to predict RFS in patients with optimally debulked EOC, which is expected to aid gynecologists in individualized prognosis assessment and clinical management.

Non-small cell lung cancer (NSCLC), the most prevalent form of lung cancer, remains a leading cause of cancer-related mortality worldwide, particularly among elderly individuals. The phenomenon of immunosenescence, characterized by the progressive decline in immune cell functionality with aging, plays a pivotal role in NSCLC progression and contributes to the diminished efficacy of therapeutic interventions in older patients. Immunosenescence manifests through impaired immune surveillance, reduced cytotoxic responses, and increased chronic inflammation, collectively fostering a pro-tumorigenic microenvironment. This review provides a comprehensive analysis of the molecular, cellular, and genetic mechanisms of immunosenescence and its impact on immune surveillance and the tumor microenvironment (TME) in NSCLC. We explore how aging affects various immune cells, including T cells, B cells, NK cells, and macrophages, and how these changes compromise the immune system's ability to detect and eliminate tumor cells. Furthermore, we address the challenges posed by immunosenescence to current therapeutic strategies, particularly immunotherapy, which faces significant hurdles in elderly patients due to immune dysfunction. The review highlights emerging technologies, such as single-cell sequencing and CRISPR-Cas9, which offer new insights into immunosenescence and its potential as a therapeutic target. Finally, we outline future research directions, including strategies for rejuvenating the aging immune system and optimizing immunotherapy for older NSCLC patients, with the goal of improving treatment efficacy and survival outcomes. These efforts hold promise for the development of more effective, personalized therapies for elderly patients with NSCLC.

To clarify the prognostic significance of the C-reactive protein to prealbumin ratio (CRP or PALB) in patients with pancreatic cancer after radical resection.

A total of 432 patients with pathologically confirmed pancreatic ductal adenocarcinoma were enrolled in this retrospective study. The predictive capacity of various inflammatory indices was analyzed and compared using the area under the time-dependent receiver operating characteristic curve, including CRP or PALB, CRP-to-albumin ratio, neutrophil-to-lymphocyte ratio, and platelet-to-lymphocyte ratio. The univariate and multivariate Cox hazard models were employed to analyze the effects of CRP or PALB on overall survival (OS) and recurrence-free survival (RFS).

The optimal cut-off value for preoperative CRP or PALB was 5.94, which was derived from the receiver operating characteristic curve. In comparison with traditional inflammatory indices, CRP or PALB had the highest area under the time-dependent receiver operating characteristic curve (0.693 for 3-y OS, 0.664 for 3-y RFS, 0.662 for 5-y OS, and 0.670 for 5-y RFS), all with P < 0.05. However, when compared with neutrophil-to-lymphocyte ratio, the predictive power of CRP or PALB was not significant for 3-y RFS (P = 0.085). Based on the results of the univariate and multivariate survival analyses, patients in the high CRP or PALB group (HCP: CRP or PALB >5.94) exhibited significantly poorer OS and RFS (median OS: 20.0 versus. 38.0 mo, P = 0.003; median RFS: 10.0 versus. 22.0 mo, P < 0.001) than those in the low CRP or PALB group (CRP or PALB ≤5.94). The multivariate analysis indicated that the HCP was independently associated with poor OS (hazard ratio (HR): 1.556, 95% confidence interval (CI) [1.089-2.222], P = 0.015) and RFS (HR: 1.551, 95% CI [1.135-2.119], P = 0.006).

The predictive capacity of preoperative CRP or PALB in pancreatic ductal adenocarcinoma patients exceeds that of traditional inflammatory indices. HCP levels are significantly correlated with a poor prognosis.

Background: The ratio of red blood cell distribution width (RDW) to platelet ratio (RPR) may have prognostic value in several inflammation-related diseases. However, few studies have been conducted on the value of RPR for predicting the severity of pyogenic liver abscess (PLA). Methods: Patients receiving the diagnosis of PLA from February 2013 to December 2022 were enrolled in this retrospective study. We collected data related to baseline characteristics and laboratory results within the first 24 hours the  of admission. The receiver operating characteristic curve and the area under the curve (AUC) were used to evaluate the predictive ability of different indicators for severity in PLA. Results: A total of 278 patients were enrolled. For the prediction of sepsis in PLA, RPR had the highest AUC (0.83; 95% confidence interval [CI], 0.78-0.89) with a sensitivity of 0.78 and specificity of 0.82. For the prediction of septic shock, RPR also had the highest AUC (0.74; 95% CI, 0.60-0.88) with a sensitivity of 0.67 and specificity of 0.79. The best cutoff value for RPR to predict sepsis was 0.08 and to predict septic shock was 0.11. Conclusions: An increase in RPR level serves as a useful indicator with a predictive capacity for severity in PLA.

Immune checkpoint inhibition (ICI) has revolutionized treatment for metastasized melanoma, but many patients remain unresponsive. Concerning potential adverse events, reliable biomarkers to predict ICI response are needed. In this context, neutrophil-to-lymphocyte ratio (NLR) and derived NLR (dNLR) have emerged. Liver metastases also limit ICI efficacy, correlating with diminished overall survival (OS) and progression-free survival (PFS) and may siphon activated T cells from the systemic circulation, creating an 'immune desert state'. We evaluated the predictive role of NLR and dNLR for ICI response and the impact of liver metastases on systemic immunity and treatment efficacy.

In this single-center retrospective study, we included 141 stage IV melanoma patients undergoing ICI. NLR and dNLR were calculated from absolute neutrophil count, absolute lymphocyte count, and white blood cell count.

Elevated NLR and dNLR were associated with poor response to ICI and inferior PFS. Patients with liver metastases exhibited higher NLR and dNLR levels and showed diminished response to ICI.

Elevated baseline NLR and dNLR predict poor response to ICI and PFS in stage IV melanoma. Liver metastases are negative predictors for ICI response, with associated higher NLR and dNLR levels potentially contributing to therapy resistance.