Preoperative peripheral blood neutrophil-to-lymphocyte ratios (NLR) and platelet-to-lymphocyte ratio (PLR) related nomograms predict the survival of patients with limited-stage small-cell lung cancer

NLR, MLR, and PLR are adverse prognostic variables for sleeve lobectomy within non-small cell lung cancer

BACKGROUND

The goal of the research was to examine the value of peripheral blood indicators in forecasting survival and recurrence among people suffering central-type non-small cell lung cancer (NSCLC) undergoing sleeve lobectomy (SL).

METHODS

Clinical information was gathered from 146 individuals suffering from NSCLC who had SL at our facility between January 2014 and May 2023. Peripheral blood neutrophil lymphocyte ratio (NLR), monocyte lymphocyte ratio (MLR), and platelet lymphocyte ratio (PLR) levels were determined by receiver operating characteristic (ROC) curve to establish the threshold points. Kaplan-Meier survival analysis was employed to evaluate the prognostic value of different groupings, and both univariate and multivariate Cox proportional hazards model (referred to as COX) were performed.

RESULTS

The disease-free survival (DFS) and overall survival (OS) cutoff values were carried out via ROC analysis. Kaplan-Meier survival analysis revealed notable differences in OS for NLR (≥2.196 vs. <2.196, p = 0.0009), MLR (≥0.2763 vs. <0.2763, p = 0.0018), and PLR (≥126.11 vs. <126.11, p = 0.0354). Similarly, significant differences in DFS were observed for NLR (≥3.010 vs. <3.010, p = 0.0005), MLR (≥0.2708 vs. <0.2708, p = 0.0046), and PLR (≥126.11 vs. <126.11, p = 0.0028). Univariate Cox analysis showed that NLR (hazard ratio [HR]: 2.469; 95% confidence interval [CI]: 1.416-4.306, p < 0.001), MLR (HR: 2.192, 95% CI: 1.319-3.643, p = 0.002) and PLR (HR: 1.696, 95% CI: 1.029-2.795, p = 0.038) were correlated alongside OS. Multivariate Cox analysis showed that NLR (HR: 2.036, 95% CI: 1.072-3.864, p = 0.030) was a separate OS risk variable. Additionally, the pN stage (HR: 3.163, 95% CI: 1.660-6.027, p < 0.001), NLR (HR: 2.530, 95% CI: 1.468-4.360, p < 0.001), MLR (HR: 2.229, 95% CI: 1.260-3.944, p = 0.006) and PLR (HR: 2.249, 95% CI: 1.300-3.889, p = 0.004) were connected to DFS. Multivariate Cox analysis showed that pN stage (HR: 3.098, 95% CI: 1.619-5.928, p < 0.001) was a separate DFS risk variable.

CONCLUSION

The study demonstrates that NLR, MLR, and PLR play a convenient and cost-effective role in predicting survival and recurrence among individuals alongside central-type NSCLC having SL.

Predictive value of dynamic changes in peripheral blood inflammation and blood lipid-related indices for the lung cancer treatment efficacy

To investigate the dynamics of inflammation and lipid-related indicators in lung cancer patients and their impact on treatment efficacy. A retrospective analysis was conducted on 133 lung cancer patients who seek for primary treatment at Wujin Hospital Affiliated to Jiangsu University from January 2019 to August 2022. The inflammation and blood lipid-related indicators were collected 1 week before treatment and after 2 cycles of treatment. We compared the changes in these indicators among patients with different treatment methods and outcomes. The diagnostic value of the dynamic changes in each index for disease progression was calculated using the ROC curve. The risk factors influencing disease development were identified using multifactorial logistic regression analysis. After 2 cycles of treatment, the white blood cell count (WBC, P<0.001), neutrophil count (NC, P<0.001), neutrophil-to-lymphocyte ratio (NLR, P<0.001) in the disease progression (PD) group were significantly increased, triglyceride (TG, P=0.023), apolipoprotein A1 (APO-A1, P=0.009) was significantly decreased. The results showed that ∆NC had the highest sensitivity (88.24%) in predicting disease progression, and ∆WBC had the best specificity (77.78%). Multivariate regression analysis showed that ΔWBC (P<0.001), ΔTG (P=0.041), and treatment method (P=0.010) were independent risk factors for disease progression (PD). The changes of WBC and TG before and after treatment are promising indicators for predicting the progression of lung cancer and may offer a new direction for lung cancer treatment.

Construction of a prognostic model for extensive-stage small cell lung cancer patients undergoing immune therapy in northernmost China and prediction of treatment efficacy based on response status at different time points

BACKGROUND AND PURPOSE

Recently, the emergence of immune checkpoint inhibitors has significantly improved the survival of patients with extensive-stage small cell lung cancer. However, not all patients can benefit from immunotherapy; therefore, there is an urgent need for precise predictive markers to screen the population for the benefit of immunotherapy. However, single markers have limited predictive accuracy, so a comprehensive predictive model is needed to better enable precision immunotherapy. The aim of this study was to establish a prognostic model for immunotherapy in ES-SCLC patients using basic clinical characteristics and peripheral hematological indices of the patients, which would provide a strategy for the clinical realization of precision immunotherapy and improve the prognosis of small cell lung cancer patients.

METHODS

This research retrospectively collected data from ES-SCLC patients treated with PD-1/PD-L1 inhibitors between March 1, 2019, and October 31, 2022, at Harbin Medical University Cancer Hospital. The study data was randomly split into training and validation sets in a 7:3 ratio. Variables associated with patients' overall survival were screened and modeled by univariate and multivariate Cox regression analyses. Models were presented visually via Nomogram plots. Model discrimination was evaluated by Harrell's C index, tROC, and tAUC. The calibration of the model was assessed by calibration curves. In addition, the clinical utility of the model was assessed using a DCA curve. After calculating the total risk score of patients in the training set, patients were stratified by risk using percentile partitioning. The Kaplan-Meier method was used to plot OS and PFS survival curves for different risk groups and response statuses at different milestone time points. Differences in survival time groups were compared using the chi-square test. Statistical analysis software included R 4.1.2 and SPSS 26.

RESULTS

This study included a total of 113 ES-SCLC patients who received immunotherapy, including 79 in the training set and 34 in the validation set. Six variables associated with poorer OS in patients were screened by Cox regression analysis: liver metastasis (P = 0.001), bone metastasis (P = 0.013), NLR < 2.14 (P = 0.005), LIPI assessed as poor (P < 0.001), PNI < 51.03 (P = 0.002), and LDH ≥ 146.5 (P = 0.037). A prognostic model for immunotherapy in ES-SCLC patients was constructed based on the above variables. The Harrell's C-index in the training and validation sets of the model was 0.85 (95% CI 0.76-0.93) and 0.88 (95% CI 0.76-0.99), respectively; the AUC values corresponding to 12, 18, and 24 months in the tROC curves of the training set were 0.745, 0.848, and 0.819 in the training set and 0.858, 0.904 and 0.828 in the validation set; the tAUC curves show that the overall tAUC is > 0.7 and does not fluctuate much over time in both the training and validation sets. The calibration plot demonstrated the good calibration of the model, and the DCA curve indicated that the model had practical clinical applications. Patients in the training set were categorized into low, intermediate, and high risk groups based on their predicted risk scores in the Nomogram graphs. In the training set, 52 patients (66%) died with a median OS of 15.0 months and a median PFS of 7.8 months. Compared with the high-risk group (median OS: 12.3 months), the median OS was significantly longer in the intermediate-risk group (median OS: 24.5 months, HR = 0.47, P = 0.038) and the low-risk group (median OS not reached, HR = 0.14, P = 0.007). And, the median PFS was also significantly prolonged in the intermediate-risk group (median PFS: 12.7 months, HR = 0.45, P = 0.026) and low-risk group (median PFS not reached, HR = 0.12, P = 0.004) compared with the high-risk group (median PFS: 6.2 months). Similar results were obtained in the validation set. In addition, we observed that in real-world ES-SCLC patients, at 6 weeks after immunotherapy, the median OS was significantly longer in responders than in non-responders (median OS: 19.5 months vs. 11.9 months, P = 0.033). Similar results were obtained at 12 weeks (median OS: 20.7 months vs 11.9 months, P = 0.044) and 20 weeks (median OS: 20.7 months vs 11.7 months, P = 0.015). Finally, we found that in the real world, ES-SCLC patients without liver metastasis (P = 0.002), bone metastasis (P = 0.001) and a total number of metastatic organs < 2 (P = 0.002) are more likely to become long-term survivors after receiving immunotherapy.

CONCLUSION

This study constructed a new prognostic model based on basic patient clinical characteristics and peripheral blood indices, which can be a good predictor of the prognosis of immunotherapy in ES-SCLC patients; in the real world, the response status at milestone time points (6, 12, and 20 weeks) can be a good indicator of long-term survival in ES-SCLC patients receiving immunotherapy.

Beyond the fractures: A comprehensive Comparative analysis of Affordable and Accessible laboratory parameters and their coefficients for prediction and Swift confirmation of pulmonary embolism in high-risk orthopedic patients

Background

Pulmonary embolism (PE) poses a significant challenge in diagnosis and treatment, particularly in high-risk patient populations such as those hospitalized for orthopedic reasons. This study explores the predictive and diagnostic potential of laboratory parameters in identifying PE among orthopedic patients.

Objectives

The purpose of this study was to determine whether selected (inexpensive and readily available) laboratory parameters and their coefficients can be used to diagnose pulmonary embolism and whether they are applicable in predicting its occurrence.

Material and methods

Selected laboratory parameters were determined twice in 276 hospitalized orthopedic patients with suspected PE: PLT, MPV, NEU, LYM, D-dimer, troponin I, age-adjusted D-dimer and their coefficients. Depending on the angio-CT results, patients were divided into groups. Selected popular laboratory coefficients were calculated and statistically analyzed. Optimal cutoff points were determined for the above laboratory tests and ROC curves were plotted.

Results

D-dimer/troponin I [p = 0.008], D-dimer [p = 0.001], age-adjusted D-dimer [p = 0.007], NLR/D-dimer [p = 0.005] and PLR [p = 0.021] are statistically significant predictors of PE. D-dimer/troponin I [p < 0.001], troponin I [p = 0.005] and age-adjusted D-dimer [p = 0.001] correlated with the diagnosis of PE after the onset of clinical symptoms.

Conclusions

In the context of orthopedic patients, cost-effective laboratory parameters, particularly the D-dimer/troponin I ratio and age-adjusted D-dimer, exhibit considerable potential in predicting and diagnosing PE. These findings suggest that combining readily available laboratory tests with clinical observation can offer a viable and cost-effective diagnostic alternative, especially in resource-constrained settings. Further studies with larger and diverse patient populations are recommended to validate these results.

Combined pretreatment neutrophil-lymphocyte ratio and platelet-lymphocyte ratio predicts survival and prognosis in patients with non-metastatic nasopharyngeal carcinoma: a retrospective study

The clinical significance of the combination of neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR) is unclear. This study investigated the predictive value of pretreatment NLR (pre-NLR) combined with pretreatment PLR (pre-PLR) for the survival and prognosis of nasopharyngeal carcinoma (NPC). A total of 765 patients with non-metastatic NPC from two hospitals were retrospectively analyzed. The pre-NLR-PLR groups were as follows: HRG, high pre-NLR and high pre-PLR. MRG, high pre-NLR and low pre-PLR or low pre-NLR and high pre-PLR. LRG, neither high pre-NLR nor high pre-PLR. Receiver operating characteristic (ROC) curves were used to identify the cutoff-value and discriminant performance of the model. We compared survival rates and factors affecting the prognosis among different groups. The 5-year overall survival (OS), local regional recurrence-free survival (LRRFS) and distant metastasis-free survival (DMFS) of NPC patients in HRG were significantly poorer than those in MRG and LRG. The pre-NLR-PLR score was positively correlated with T stage, clinical stage, ECOG, and pathological classification. Multivariate cox regression analysis showed that pre-NLR-PLR scoring system, ECOG, pre-ALB, pre-CRP and pre-LMR were independent risk factors affecting 5-year OS, LRRFS and DMFS. The ROC curve showed that area under the curve (AUC) values of pre-NLR-PLR of 5-year OS, LRRFS and DMFS were higher than those of pre-NLR and pre-PLR. pre-NLR-PLR is an independent risk factor for the prognosis of NPC. The pre-NLR-PLR scoring system can be used as an individualized clinical assessment tool to predict the prognosis of patients with non-metastatic NPC more accurately and easily.

Preoperative sarcopenia combined with prognostic nutritional index predicts long-term prognosis of radical gastrectomy with advanced gastric cancer: a comprehensive analysis of two-center study

PURPOSE

This study aims to investigate the predictive value of the combined index smni(skeletal muscle index (SMI)-prognostic nutrition index(PNI)) for the postoperative survival of patients with advanced gastric cancer(AGC).

METHODS

650 patients with AGC from two centers (290 cases from the First Affiliated Hospital of Dalian University and 360 points from the Fujian Medical University Union Hospital) were selected as the study subjects based on unified screening criteria. Clinical data, preoperative abdominal CT images, results of hematology-related examinations, tumor-related characteristics, and surgical and follow-up data of the patients were collected and organized. The L3 vertebral level muscle area was measured using computer-assisted measurement techniques, and the skeletal muscle index(SMI) was calculated based on this measurement. The prognostic nutrition index (PNI) was calculated based on serum albumin and lymphocyte count indicators. The Kaplan-Meier survival analysis of data from the First Affiliated Hospital was used to determine that SMI and PNI are significantly correlated with the postoperative survival rate of patients with advanced gastric cancer. Based on this, a novel combined index smni was fitted and stratified for risk. Cox proportional hazards regression analysis was used to determine that the index smni is an independent prognostic risk factor for patients with AGC after surgery. The ROC curve was used to describe the predictive ability of the new combined index and its importance and predictive power in predicting postoperative survival of patients with AGC, which was verified in the data of Fujian Medical University Union Hospital.

RESULT

The Kaplan-Meier curve analysis of the combined indicator smni Is clearly associated with long-term survival(3-year OS (P < 0.001) and DSS (P < 0.001)), univariate analysis and multivariate analysis showed that smni was an independent prognostic risk factor, The ROC curve for the first center 3-year OS(AUC = 0.678), DSS(AUC = 0.662) show good predictive ability and were validated in the second center.

CONCLUSION

The combined index smni has a good predictive ability for the postoperative survival rate of patients with AGC and is expected to provide a new reference basis and more accurate and scientific guidance for the postoperative management and treatment of patients with AGC.

Evaluation of multiple biological indicators for the combined diagnosis of metastases from colorectal cancer-a retrospective study based on 1163 patients

OBJECTIVE

This study aimed to investigate the efficacy of inflammatory markers (NLR, PLR) combined with tumor markers (CA50, CA199, CEA) in the diagnosis of colorectal cancer metastasis by a single-center retrospective study.

METHODS

A total of 1163 CRC patients who received treatments in our hospital from January 2017 to December 2021 were enrolled retrospectively. Patients were grouped according to the absence of metastasis. The separate efficacy of tumor markers, NLR and PLR, was evaluated in the diagnosis of metastasis of colorectal cancer using ROC curve analysis, and their optimal cut-off values for distant metastases from colorectal cancer were determined. The area under the ROC curve (AUC) of the tumor markers combined with NLR and PLR was calculated by binary logistic regression analysis to evaluate the diagnostic efficacy of metastasis of colorectal cancer. In addition, patients were divided into two groups of high and low levels according to the optimal cut-off values, and the effects of NLR, PLR, and tumor markers on distant metastasis of colorectal cancer were evaluated using multiple logistic regression analysis.

RESULT

The abnormal rate of CA50, CA199, CEA, NLR, and PLR in two subgroupsIt was statistically significant (P < 0.05). After AUC testifying, the diagnostic efficacy of NLR and PLR was equivalent to that of tumor marker (P > 0.05). In assessment of liver metastasis, peritoneal metastasis, and multiple metastasis, AUC of NLR and PLR with CRC-specific tumor markers showed higher predictive efficacy than AUC without combined NLR nor PLR. The CA50, CA199, CEA, PLR, and NLR were proved independently associated with metastasis using multiple logistic regression analysis (P < 0.05).

CONCLUSION

NLR and PLR are noted tumor markers of colorectal cancer, which are characterized by noninvasive, high diagnostic efficacy, easy availability, and low cost. They can be combined with traditional tumor markers to evaluate and diagnose colorectal cancer metastasis by clinicians.

Common nutritional/inflammatory indicators are not effective tools in predicting the overall survival of patients with small cell lung cancer undergoing first-line chemotherapy

Objective

Various studies have investigated the predictive significance of numerous peripheral blood biomarkers in patients with small cell lung cancer (SCLC). However, their predictive values have not been validated. This study assessed and evaluated the ability of common nutritional or inflammatory indicators to predict overall survival (OS) in patients with SCLC who received first-line chemotherapy.

Methods

Between January 2008 and July 2019, 560 patients with SCLC were enrolled at the Sichuan University West China Hospital. Eleven nutritional or inflammatory indices obtained before chemotherapy were evaluated. The cutoff values of continuous peripheral blood indices were confirmed through maximally selected rank statistics. The relationship of peripheral blood indices with OS was investigated through univariate and multivariate Cox regression analyses. Harrell's concordance (C-index) and time-dependent receiver operating characteristic curve were used to evaluate the performance of these indices.

Results

A total of 560 patients with SCLC were enrolled in the study. All the patients received first-line chemotherapy. In the univariate Cox analysis, all indices, except the Naples score, were related to OS. In the multivariate analysis, albumin-globulin ratio was an independent factor linked with prognosis. All indices exhibited poor performance in OS prediction, with the area under the curve ranging from 0.500 to 0.700. The lactic dehydrogenase (LDH) and prognostic nutritional index (PNI) were comparatively superior predictors with C-index of 0.568 and 0.550, respectively. The LDH showed incremental predictive values, whereas the PNI showed diminishing values as survival time prolonged, especially for men or smokers. The LDH with highest sensitivity (0.646) and advanced lung cancer inflammation index (ALI) with highest specificity (0.952) were conducive to identifying death and survival at different time points.

Conclusion

Common inflammatory or nutritional biomarkers are only marginally useful in predicting outcomes in patients with SCLC receiving first-line chemotherapy. Among them, LDH, PNI, and ALI are relatively promising biomarkers for prognosis evaluation.

Association of prognostic nutritional index with prognostic outcomes in patients with glioma: a meta-analysis and systematic review

Background

The potential link between Prognostic Nutritional Index (PNI) and prognosis in patients with glioma remains uncertain. This meta-analysis was conducted to assess the clinical value of PNI in glioma patients by integrating all available evidence to enhance statistical power.

Method

A systematic search of databases including Medline, EMBASE, Google Scholar, and Cochrane Library was conducted from inception to January 8, 2023 to retrieve all pertinent peer-reviewed articles. The primary outcome of the study was to examine the association between a high PNI value and overall survival, while secondary outcome included the relationship between a high PNI and progression-free survival.

Results

In this meta-analysis, we included 13 retrospective studies published from 2016 to 2022, which analyzed a total of 2,712 patients. Across all studies, surgery was the primary treatment modality, with or without chemotherapy and radiotherapy as adjunct therapies. A high PNI was linked to improved overall survival (Hazard Ratio (HR) = 0.61, 95% CI: 0.52 to 0.72, p < 0.00001, I2 = 25%), and this finding remained consistent even after conducting sensitivity analysis. Subgroup analyses based on ethnicity (Asian vs. non-Asian), sample size (<200 vs. >200), and source of hazard ratio (univariate vs. multivariate) yielded consistent outcomes. Furthermore, patients with a high PNI had better progression-free survival than those with a low PNI (HR=0.71, 95% CI: 0.58 to 0.88, p=0.001, I2 = 0%).

Conclusion

Our meta-analysis suggested that a high PNI was associated with better overall survival and progression-free survival in patients with glioma. These findings may have important implications in the treatment of patients with glioma. Additional studies on a larger scale are necessary to investigate if integrating the index into the treatment protocol leads to improved clinical outcomes in individuals with glioma.

Systematic review registration

[https://www.crd.york.ac.uk/prospero/], identifier [CRD42023389951].

Blood inflammatory biomarkers in participants with idiopathic epiretinal membrane: A retrospective case series study

The objective was to evaluate the levels of monocyte-to-lymphocyte ratio (MLR), neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) in patients with idiopathic epiretinal membrane (iERM). This retrospective case series study comprised of participants with iERM and participants with cataract. The values of MLR, NLR, PLR and from participants' peripheral blood were assessed among groups. The best cutoff value of MLR, NLR, and PLR in iERM was found by performing a receiver operating characteristic curve analysis and determining the optimum cutoff value for each variable. In total, 95 participants with iERM were included in the study group, and 61 participants with senile cataract were included as controls. The lymphocyte count in the iERM group was significantly lower than the control group (1.69 ± 0.63 vs. 1.95 ± 0.53, P = .003). The monocyte count in the iERM group was significantly higher than the control group (0.39 ± 0.11 vs. 0.31 ± 0.10, P < .001). The area under the curve of MLR, NLR, and PLR in differentiating patients with IERM and controls was 0.782, 0.645, and 0.657, respectively, according to receiver operating characteristic. The best cutoff value of MLR was > 0.18, with sensitivity and specificity of 74.7% and 75.4%, respectively. The NLR was > 2.06, with a sensitivity and specificity of 50.5% and 83.6%, respectively. The PLR was > 95.89, with a sensitivity and specificity of 86.3% and 41.0%, respectively. The findings of this study suggest that systemic inflammation may be associated with iERM. IERM patients may be prone to have high MLR, NLR, and PLR values.

The Prognostic Value and Potential Mechanism of Tumor-Nutrition-Inflammation Index and Genes in Patients with Advanced Lung Cancer

Background

Lung cancer (LC) has the highest mortality rate all over the world. It is necessary to search for novel potential biomarkers that are easily accessible and inexpensive in identifying patients with LC at early stage.

Methods

A total of 195 patients with advanced LC who have received first-line chemotherapy were involved in this study. The optimized cut-off values of AGR and SIRI (AGR = albumin/globulin; SIRI = neutrophil ∗ monocyte/lymphocyte) were determined by survival function analysis based on R software. COX regression analysis was performed to obtain the independent factors for establishing the nomogram model. A nomogram model comprising these independent prognostic parameters was built for the TNI (tumor-nutrition-inflammation index) score calculation. The predictive accuracy was demonstrated through ROC curve and calibration curves after index concordance.

Results

The optimized cut-off values of AGR and SIRI were 1.22 and 1.60, respectively. It was revealed that liver metastasis, SCC, AGR, and SIRI were independent prognostic factors in advanced lung cancer by Cox analysis. Afterwards, the nomogram model comprised of these independent prognostic parameters was built for TNI scores calculation. Based on the TNI quartile values, patients were divided into four groups. And it was indicated that higher TNI had worse OS (P < 0.05) via Kaplan-Meier analysis and log-rank test. Moreover, the C-index and 1-year AUC area were 0.756 (0.723-0.788) and 75.62, respectively. There was high consistency shown in the calibration curves between predicted and actual survival proportions in the TNI model. In addition, tumor-nutrition-inflammation index and genes play an important role in LC development that might affect some pathways related to tumor development including cell cycle, homologous recombination, and P53 signaling pathway from a molecular level.

Conclusion

TNI might be an analytical tool which was practical and precise for survival prediction of patients with advanced LC. Tumor-nutrition-inflammation index and genes play an important role in LC development. A preprint has previously been published [1].

Construction of the prognostic model for small-cell lung cancer based on inflammatory markers: A real-world study of 612 cases with eastern cooperative oncology group performance score 0-1

OBJECTIVES

This research aimed to explore the relationship between pre-treatment inflammatory markers and other clinical characteristics and the survival of small-cell lung cancer (SCLC) patients who received first-line platinum-based treatment and to construct nomograms for predicting overall survival (OS) and progression-free survival (PFS).

METHODS

A total of 612 patients diagnosed with SCLC between March 2008 and August 2021 were randomly divided into two cohorts: a training cohort (n = 459) and a validation cohort (n = 153). Inflammatory markers, clinicopathological factors, and follow-up information of patients were collected for each case. Cox regression was used to conduct univariate and multivariate analyses and the independent prognostic factors were adopted to develop the nomograms. Harrell's concordance index (C-index) and time-dependent receiver operating characteristic curve were used to verify model differentiation, calibration curve was used to verify consistency, and decision curve analysis was used to verify the clinical application value.

RESULTS

Our results showed that baseline C-reactive protein/albumin ratio, neutrophil/lymphocyte ratio, NSE level, hyponatremia, the efficacy of first-line chemotherapy, and stage were independent prognostic factors for both OS and PFS in SCLC. In the training cohort, the C-index of PFS and OS was 0.698 and 0.666, respectively. In the validation cohort, the C-index of PFS and OS was 0.727 and 0.747, respectively. The nomograms showed good predictability and high clinical value. Also, our new clinical models were superior to the US Veterans Administration Lung Study Group (VALG) staging for predicting the prognosis of SCLC.

CONCLUSIONS

The two prognostic nomograms of SCLC including inflammatory markers, VALG stage, and other clinicopathological factors had good predictive value and could individually assess the survival of patients.

Association and prediction of red blood cell distribution width to albumin ratio in all-cause mortality of acute kidney injury in critically ill patients

Aim

The progression of acute kidney injury (AKI) might be associated with systemic inflammation. Our study aims to explore the association and predictive value of the red blood cell distribution width (RDW) to human serum albumin (ALB) ratio (RDW/ALB ratio), an inflammation-related indicator, in the risk of all-cause mortality and renal replacement therapy (RRT) in AKI patients admitted in intensive care units (ICU).

Methods

A retrospective cohort study was designed, and data were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III). The primary outcome was the risk of all-cause mortality (1-month, 3-month, and 12-month), and the secondary outcome was the risk of RRT. The association between the RDW/ALB ratio and the risk of all-cause mortality and RRT was assessed using the Cox regression analysis, with results shown as hazard ratio (HR) and 95% confidence intervals (CIs). The relationship between the RDW/ALB ratio and crude probability of all-cause mortality or RRT was assessed using restricted cubic splines (RCS). The concordance index (C-index) was used to assess the discrimination of the prediction model.

Results

A total of 13,856 patients were included in our study. In the fully adjusted Cox regression model, we found that a high RDW/ALB ratio was associated with an increased risk of 1-month, 3-month, and 12-month all-cause mortality and RRT (all p &lt; 0.05). Moreover, RCS curves showed the linear relationship between the RDW/ALB ratio and the probability of all-cause mortality and RRT, and the probability was elevated with the increase of the ratio. In addition, the RDW/ALB ratio showed a good predictive performance in the risk of 1-month all-cause mortality, 3-month all-cause mortality, 12-month all-cause mortality, and RRT, with a C-index of 0.728 (95%CI: 0.719–0.737), 0.728 (95%CI: 0.721–0.735), 0.719 (95%CI: 0.713–0.725), and 0.883 (95%CI: 0.876–0.890), respectively.

Conclusion

The RDW/ALB ratio performed well to predict the risk of all-cause mortality and RRT in critically ill patients with AKI, indicating that this combined inflammatory indicator might be effective in clinical practice.

Combined use of CA125, neutrophil/lymphocyte ratio and platelet/lymphocyte ratio for the diagnosis of borderline and malignant epithelial ovarian tumors

BACKGROUND

The mortality rate of ovarian cancer ranks first among three common gynecological malignant tumors due to insidious onset and lack of effective early diagnosis methods. Borderline epithelial ovarian tumor (BEOT) is a type of low malignant potential tumor that is typically associated with better outcomes than ovarian cancer. However, BEOTs are easily confused with benign and malignant epithelial ovarian tumors (EOTs) due to similar clinical symptoms and lack of specific tumor biomarkers and imaging examinations. Notably, a small subset of BEOTs will transform into low-grade serous ovarian carcinoma with a poor prognosis. Therefore, searching for potential biomarkers that can be easily obtained and accurately identify malignant epithelial ovarian tumors (MEOTs) as well as BEOTs is essential for the clinician. Cancer antigen 125 (CA125) is a commonly used biomarker for the diagnosis of EOTs in the preoperative scenario but has low sensitivity and specificity. Nowadays, inflammatory biomarkers including inflammatory cell counts and derived ratios such as neutrophil/lymphocyte ratio (NLR) and platelet/lymphocyte ratio (PLR) have been proved to be associated with tumor progression and poor prognosis, and were considered to be the most economically potential surrogate biomarkers for various malignancies. The purpose of this study was to find appropriate combinations of inflammatory and tumor biomarkers to improve the diagnostic efficiency of EOTs, especially the BEOTs.

RESULTS

CA125, NLR and PLR increased steadily among benign, borderline and malignant EOTs and tended to be higher in advanced (stage III-IV) and lymph node metastasis MEOT groups than in early stage (stage I-II) and non-lymph node metastasis MEOT groups. CA125, NLR and PLR could be used separately in the differentiation of EOTs but could not take into account both sensitivity and specificity. The combined use of CA125, NLR and PLR was evaluated to be more efficient, especially in the identification of BEOTs, with both high sensitivity and high specificity.

CONCLUSIONS

The levels of CA125, NLR and PLR were closely related to the nature of EOTs and malignant progression of MEOTs. The combination of CA125, NLR and PLR was more accurate in identifying the nature of EOTs than either alone or double combination, especially for BEOTs.

Platelet-lymphocyte ratio is a prognostic marker in small cell lung cancer-A systemic review and meta-analysis

Aim

The aim of this study was to evaluate the relationship between platelet-lymphocyte ratio (PLR) and prognosis in small cell lung cancer (SCLC) patients.

Method

A comprehensive search was carried out to collect related studies. Two independent investigators extracted the data of hazard ratio (HR) and 95% confidence interval (CI) for overall survival (OS) or progression-free survival (PFS). A random-effect model was applied to analyze the effect of different PLR levels on OS and PFS in SCLC patients. Moreover, subgroup analysis was conducted to seek out the source of heterogeneity.

Results

A total of 26 articles containing 5,592 SCLC patients were included for this meta-analysis. SCLC patients with a high PLR level had a shorter OS compared with patients with a low PLR level, in both univariate (HR = 1.56, 95% CI 1.28-1.90, p < 0.0001) and multivariate (HR = 1.31, 95% CI 1.08-1.59, p = 0.007) models. SCLC patients with a high PLR level had a shorter PFS compared with patients with a low PLR level, in the univariate model (HR = 1.71, 95% CI 1.35-2.16, p < 0.0001), but not in the multivariate model (HR = 1.17, 95% CI 0.95-1.45, p = 0.14). Subgroup analysis showed that a high level of PLR shortened OS in some subgroups, including the Asian subgroup, the younger subgroup, the mixed-stage subgroup, the chemotherapy-dominant subgroup, the high-cutoff-point subgroup, and the retrospective subgroup. PLR level did not affect OS in other subgroups.

Conclusion

PLR was a good predictor for prognosis of SCLC patients, especially in patients received chemotherapy dominant treatments and predicting OS.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42022383069.

The Systemic Inflammation Score is Associated with the Survival of Patients with Prostate Cancer

Background

The systemic inflammation score (SIS) based on the albumin (Alb) level and lymphocyte-to-monocyte ratio (LMR), has been associated with survival in some cancers. However, its prognostic role in prostate cancer (PCa) remains unclear.

Methods

The associations between the SIS and the clinicopathological features of PCa were evaluated. The correlations between the SIS and overall survival (OS) and progression-free survival (PFS) were assessed using Kaplan-Meier analysis and the Log rank test. Univariate and multivariate Cox analyses were conducted to determine the prognostic factors for PCa. Hazard ratios and 95% confidence intervals were calculated.

Results

A total of 253 patients with PCa were included in this study. The Kaplan-Meier analysis and Log rank test suggested that patients with a higher Alb level, higher LMR, or a lower SIS had better 5-year OS and PFS compared with patients with a lower Alb level or lower LMR or higher SIS. Univariate and multivariate Cox analyses showed that drinking, prostate-specific antigen level >100 ng/mL, and neutrophil-to-lymphocyte ratio >2.09 were significant prognostic factors for OS and PFS in patients with PCa. Nomograms for 5-year OS and PFS were established with concordance index values of 0.888 and 0.824, respectively. The calibration curve was consistent between the actual observations and the prediction nomogram for OS and PFS probability at 5 years.

Conclusion

A high SIS is associated with unfavorable survival in patients with PCa. The SIS serves as a novel independent prognostic factor for OS in patients with PCa.

A Novel Nomogram Integrated with Systemic Inflammation Markers and Traditional Prognostic Factors for Adverse Events' Prediction in Patients with Chronic Heart Failure in the Southwest of China

Objective

Inflammation contributes to the pathogenesis and progression of heart failure (HF). This study aimed to construct a nomogram based on systemic inflammatory markers and traditional prognostic factors to assess the risk of adverse outcomes (cardiovascular readmission and all-cause death) in patients with chronic heart failure (CHF).

Methods

Data were retrospectively collected from patients with HF admitted to the Department of Cardiovascular Medicine at the First Affiliated Hospital of Chongqing Medical University from January 2018 to April 2020, and each patient had complete follow-up information. The follow-up duration was from June 2018 to May 31, 2022. 550 patients were included and randomly assigned to the derivation and validation cohorts with a ratio of 7:3, and prognostic risk factors of CHF were identified by Cox regression analysis. The nomogram chart scoring model was constructed.

Results

The Cox multivariate regression analysis showed that traditional prognostic factors such as age (P=0.011), BMI (P=0.048), NYHA classification (P<0.001), creatinine (P<0.001), and systemic inflammatory markers including LMR (P=0.001), and PLR (P=0.015) were independent prognostic factors for CHF patients. Integrated with traditional and inflammatory prognostic factors, a nomogram was established, which yielded a C-index value of 0.739 (95% CI: 0.714-0.764) in the derivation cohort and 0.713 (95% CI: 0.668-0.758) in the validation cohort, respectively. The calibration curves exhibited good performance of the nomogram in predicting the adverse outcomes for patients with CHF. In subgroups (HFrEF, HFmrEF, and HFpEF groups), the systematic inflammatory markers-based nomograms proved to be effective prediction tools for patients' adverse overcomes, as well.

Conclusion

The nomogram combining systemic inflammatory markers and traditional risk factors has satisfactory predictive performance for adverse outcomes (mortality and readmission) in patients with CHF.

The predictive value of the preoperative systemic immune-inflammation index in the occurrence of postoperative pneumonia in non-small cell lung cancer: A retrospective study based on 1486 cases

BACKGROUND

To investigate the correlation between the preoperative systemic immune-inflammation index (pSII) and postoperative pneumonia (POP) in surgical non-small cell lung cancer patients.

METHODS

Patients who underwent lung cancer surgery at West China Hospital of Sichuan University were retrospectively included. The indicators were collected, including basic information of patients, surgery-related variables and POP rate. The predictive value of the pSII in the occurrence of POP was analyzed.

RESULTS

A total of 1486 patients (male: 748, 50.3%; female: 738, 49.7%; mean age: 58.2 ± 9.7 years; median age: 59 years old, interquartile range: 51-65 years old) were finally included in the study, of which 142 patients had POP with an incidence of 9.5% (142/1486), 9.2% (69/748) in males, and 9.9% (73/738) in females. The proportion of patients with diabetes in the pneumonia group was significantly higher than that in the nonpneumonia group (9.8%, 14/142 vs. 5.6%, 75/1344, p = 0.041). Compared with the nonpneumonia group, the level of the preoperative body mass index (24.2 [21.9, 26.1] vs. 23.1 [21.1, 25.2], p = 0.003) and SII (487 [350, 673] vs. 345 [230, 500], p < 0.001) in the pneumonia group were significantly higher. Multiple factor analysis showed that the pSII (odds ratio: 1.001, 95% confidence interval: 1.000-1.001, p < 0.001) was an independent risk factor for POP (487 [350, 673] vs. 345 [230, 500], p < 0.001); receiver operating characteristic curve analysis showed that the pSII was effective in predicting POP (area under curve: 0.751, p < 0.001).

CONCLUSION

The pSII is closely related to and can effectively predict the occurrence of POP after lung cancer surgery.

Inflammation-based prognostic scoring system for predicting the prognosis of advanced small cell lung cancer patients receiving anlotinib monotherapy

BACKGROUND

According to the randomized multicenter phase II trial (ALTER1202), anlotinib has been approved as a third-line therapy for advanced small-cell lung cancer (SCLC). Some studies showed the predictive function of inflammatory markers, including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR) in the different cancers treated with anti-vascular targeting drugs. However, none of the studies showed the roles of NLR, PLR, and LMR in SCLC patients receiving anlotinib. Thus, our objective was to establish a scoring system based on inflammation to individuate patient stratification and selection based on NLR, PLR, and LMR.

METHODS

NLR, PLR, and LMR and their variations were calculated in 53 advanced SCLC patients receiving anlotinib as a third- or further-line treatment at Ningbo Medical Center Lihuili Hospital between January 2019 and December 2021. Kaplan-Meier curves were plotted. Both univariate and multivariate Cox regressions were used to identify predictors of survival.

RESULTS

Disease control rate was related to pre-NLR, pre-PLR, pre-LMR, post-NLR elevation, post-PLR elevation, and post-LMR elevation. The multivariate analysis determined post-NLR elevation, pre-PLR > 240.56, and pre-LMR ≤1.61 to be independently associated with progression-free survival, not overall survival. The inflammation-based prognostic scoring system demonstrated favorable predictive ability from the receiver operating characteristic curve (AUC: 0.791, 95% CI: 0.645-0.938).

CONCLUSIONS

Post-NLR variation, pre-PLR, and pre-LMR were independent prognostic factors for PFS in advanced SCLC receiving anlotinib monotherapy. The inflammation-based prognostic scoring system can accurately predict effectiveness and survival.

Ferroptosis, necroptosis, and pyroptosis in the tumor microenvironment: Perspectives for immunotherapy of SCLC

Small cell lung cancer (SCLC) is an aggressive form of lung cancer characterized by dismal prognosis. Although SCLC may initially respond well to platinum-based chemotherapy, it ultimately relapses and is almost universally resistant to this treatment. Immune checkpoint inhibitors (ICIs) have been approved as the first- and third-line therapeutic regimens for extensive-stage or relapsed SCLC, respectively. Despite this, only a minority of patients with SCLC respond to ICIs partly due to a lack of tumor-infiltrating lymphocytes (TILs). Transforming the immune "cold" tumors into "hot" tumors that are more likely to respond to ICIs is the main challenge for SCLC therapy. Ferroptosis, necroptosis, and pyroptosis represent the newly discovered immunogenic cell death (ICD) forms. Promoting ICD may alter the tumor microenvironment (TME) and the influx of TILs, and combination of their inducers and ICIs plays a synergistical role in enhancing antitumor effects. Nevertheless, the combination of the above two modalities has not been systematically discussed in SCLC therapy. In the present review, we summarize the roles of distinct ICD mechanisms on antitumor immunity and recent advances of ferroptosis-, necroptosis- and pyroptosis-inducing agents, and present perspectives on these cell death mechanisms in immunotherapy of SCLC.

A Nomogram Based on Hematological Parameters and Clinicopathological Characteristics for Predicting Local–Regional Recurrence After Breast-Conserving Therapy

Objectives

The aim of this study was to identify the factors for local–regional recurrence (LRR) after breast-conserving therapy (BCT). We established a practical nomogram to predict the likelihood of LRR after BCT based on hematological parameters and clinicopathological features.

Methods

A retrospective analysis was performed on 2,085 consecutive breast cancer patients who received BCT in Shandong Cancer Hospital from 2006 to 2016, including 1,460 patients in the training cohort and 625 patients in the validation cohort. Univariate and multivariate analyses were performed based on hematological parameters (fibrinogen, platelets, mean platelet volume, neutrophils, monocytes, and lymphocytes) and clinicopathological characteristics to identify the independent factors for LRR. Subsequently, a nomogram for predicting LRR was established by logistic regression analysis. The nomogram was validated in 625 patients in the validation cohort.

Results

During the median follow-up period of 66 months, 44 (3.01%) patients in the training cohort and 19 (3.04%) patients in the validation cohort suffered from LRR. Multivariate analysis showed six independent factors related to LRR, including molecular subtype, pathological N stage, re-resection, radiotherapy or not, platelet count*MPV*fibrinogen (PMF), and neutrophil count/lymphocyte count ratio (NLR). Six variables were entered into logistic regression to establish the nomogram for predicting LRR. The nomogram of LRR showed excellent discrimination and prediction accuracy. The area under the receiver operating characteristic curve (AUC) was 0.89 (p < 0.001, 95% CI = 0.83, 0.95) in the training cohort and 0.88 (p < 0.001, 95% CI = 0.8, 0.96) in the validation cohort. Calibration curves for the prediction model in the training and validation cohorts both demonstrated satisfactory consistency between the nomogram-predicted and actual LRR.

Conclusion

The combination of hematological parameters and clinicopathological characteristics can predict LRR after BCT. The predictive nomogram based on preoperative and postoperative indicators of BCT might serve as a practical tool for individualized prognostication. More prospective studies should be performed to verify the model.

Risk Prediction Model for Synchronous Oligometastatic Non-Small Cell Lung Cancer: Thoracic Radiotherapy May Not Prolong Survival in High-Risk patients

Background and Purpose

On the basis of the promising clinical study results, thoracic radiotherapy (TRT)¹ has become an integral part of treatment of synchronous oligometastatic non–small cell lung cancer (SOM-NSCLC). However, some of them experienced rapid disease progression after TRT and showed no significant survival benefit. How to screen out such patients is a more concerned problem at present. In this study, we developed a risk-prediction model by screening hematological and clinical data of patients with SOM-NSCLC and identified patients who would not benefit from TRT.

Materials and Methods

We investigated patients with SOM-NSCLC between 2011 and 2019. A formula named Risk-Total was constructed using factors screened by LASSO-Cox regression analysis. Stabilized inverse probability treatment weight analysis was used to match the clinical characteristics between TRT and non-TRT groups. The primary endpoint was overall survival (OS).

Results

We finally included 283 patients divided into two groups: 188 cases for the training cohort and 95 for the validation cohort. Ten prognostic factors included in the Risk-Total formula were age, N stage, T stage, adrenal metastasis, liver metastasis, sensitive mutation status, local treatment status to metastatic sites, systemic inflammatory index, CEA, and Cyfra211. Patients were divided into low- and high-risk groups based on risk scores, and TRT was found to have improved the OS of low-risk patients (46.4 vs. 31.7 months, P = 0.083; 34.1 vs. 25.9 months, P = 0.078) but not that of high-risk patients (14.9 vs. 11.7 months, P = 0.663; 19.4 vs. 18.6 months, P = 0.811) in the training and validation sets, respectively.

Conclusion

We developed a prediction model to help identify patients with SOM-NSCLC who would not benefit from TRT, and TRT could not improve the survival of high-risk patients.

Changes in Neutrophil to Lymphocyte Ratio, Lymphocyte to Monocyte Ratio, and Platelet to Lymphocyte Ratio During Palliative Radiotherapy May Predict Efficacy of Immune Checkpoint Inhibitor as Re-Challenge Treatment in Advanced Gastric Cancer: A Case Report

Introduction

Immunotherapy with programmed death-1 (PD-1) inhibitors has emerged as frontline option in patients with advanced or metastatic gastric cancer. However, two-thirds of patients who received PD-1 inhibitors treatment still had disease progression in 1 year. Subsequent treatment strategies as salvage options always lead to limited efficacy.

Case Description

Herein, we presented a case of recurrent metastatic gastric adenocarcinoma that had progressed on first-line treatment with nivolumab, in which systematic inflammation parameters with neutrophil to lymphocyte ratio (NLR), lymphocyte to monocyte ratio (LMR), and platelet to lymphocyte ratio (PLR) were significantly changed by palliative radiotherapy on metastatic lymph nodes. The patient achieved persistent response to the re-challenge of immune checkpoint inhibitor, which resulted in survival time reaching 52 months, and is still in extension.

Conclusions

We supposed that the palliative radiotherapy may lead to the correction of NLR, LMR, and PLR and finally contribute to the efficacy of the re-challenge treatment by PD-1 inhibitor.

External Application of a Nomogram to Predict Survival and Benefit of Peripheral Blood Inflammatory Indexes in Limited-Stage Small Cell Lung Cancer

Background

Qi et al. recently proposed a nomogram to reveal the prognostic value of peripheral blood inflammatory indexes (named Risk) and predict overall survival (OS) in limited-stage small cell lung cancer (LS-SCLC). However, it hasn’t undergone external application so far. This study aimed to verify the role of Risk as a prognostic variable of OS and apply the nomogram externally.

Methods

We used a retrospective analysis of clinical data of 254 patients diagnosed as LS-SCLC in Shanxi Cancer Hospital from January 2015 to December 2018 to apply Qi’s nomogram externally. We also performed subgroup analysis to explore the predictive value of Risk. The model was evaluated in terms of discrimination (the area under the ROC curve (AUC ROC) and calibration (calibration plots).

Results

The prognosis of patients with low-Risk was significantly better than those with high-Risk in our cohort (p<0.01). The AUC of 1-, 2-, and 3-year OS was 0.644, 0.666, and 0.635, respectively. The calibration curve showed a nearly ideal calibration-slope of 1-, 2-, and 3-year OS (1.00 (0.41-1.59), 1.00 (0.54-1.46) and 1.00 (0.43-1.57), respectively).

Conclusion

The external application of nomogram added Risk for predicting OS in LS-SCLC patients showed a moderate-to-good performance using a cohort with different case-mix characteristics. The external application confirmed the predictive value of Risk and the usefulness of the nomogram for the prediction of OS.

Correlation analysis of lymphocyte-monocyte ratio with pathological complete response and clinical prognosis of neoadjuvant chemotherapy in patients with breast cancer

•

We evaluated the impact of LMR on pCR and prognosis in breast cancer patients.

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High LMR predicts increased pCR in HER2(+) breast cancer patients.

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High LMR predicts a better prognosis in neoadjuvant chemotherapy patients.

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LMR is an economical and easy detection index for patients.

Purpose

Inflammation plays an important role in tumor proliferation, metastasis, and chemotherapy resistance. Peripheral blood lymphocyte-monocyte ratio (LMR) has been reported to be closely associated with the prognosis of many tumors, such as certain hematologic malignancies and gastric cancer. However, the association in breast cancer is still not clear. This study investigated the relationship between LMR with pathological complete response and clinical prognosis of neoadjuvant chemotherapy in patients with breast cancer, to provide convenient and accurate predictive indicators for pathological complete response (pCR) and prognosis.

Methods

The clinicopathological data of 192 female breast cancer patients who received neoadjuvant chemotherapy and surgery in Harbin Medical University Tumor Hospital from January 2013 to August 2017 were retrospectively analyzed. Blood lymphocytes and monocytes were obtained by peripheral venous punctures.

Results

Compared with the low LMR group, pCR was more easily obtained in the high LMR group (P=0.020); Subgroup analysis showed that patients with the high LMR and HER-2(+) group were more likely to obtain pCR (P=0.011).Univariate andmultivariate results showed that the overall survival (OS) and disease free survival (DFS) of the high LMR group were longer than that of the low LMR group.

Conclusion

LMR and HER-2 status are correlated with pCR of neoadjuvant chemotherapy in breast cancer patients and are independent predictors of pCR after neoadjuvant chemotherapy in breast cancer patients. Meanwhile, both LMR and T stage of tumor are independent prognostic factors of breast cancer patients, with good predictive value.

Peripheral Tumor Location Predicts a Favorable Prognosis in Patients with Resected Small Cell Lung Cancer

BACKGROUND

Small cell lung cancer (SCLC) is an aggressive malignancy. Surgical resection is currently only recommended for clinical stage I patients who have been carefully staged. The clinical outcomes of patients with resected SCLCs vary because the disease is highly heterogeneous, suggesting that selected patients could be considered for surgical resection depending on their clinical and/or molecular characteristics.

METHODS

We collected data on a retrospective cohort of 119 limited-stage SCLC patients who underwent lobectomy with mediastinal lymph node dissection from March 2013 to March 2020 at Harbin Medical University Cancer Hospital. Correlations were derived using Fisher's exact test. Models of 2-year and 3-year survival were evaluated by deriving the area under receiver operating characteristic curves. Kaplan-Meier and Cox regression analyses were used to evaluate significant differences between the survival curves and hazard ratios.

RESULTS

The median disease-free survival (DFS) was 35.9 months (range 0.9-105.3 months), and the median overall survival (OS) was 45.2 months (range 4.8-105.3 months). Univariate analysis showed that TNM stage was significantly correlated with DFS and OS. The 2-year disease-free rates of patients with stage I, II, and III disease were 76.4%, 50.5%, and 36.1%, respectively, and the 3-year OS rates were 75.9%, 57.7%, and 34.4%, respectively. In pN + patients, multiple (or multiple-station) lymph node involvement significantly increased recurrence and reduced survival compared with patients with single or single-station metastases. Patients with peripheral SCLCs evidenced significantly better DFS and OS than did patients with central tumors. Multivariate analysis showed that TNM stage and tumor location were independently prognostic in Chinese patients with resected limited-stage SCLC. A combination of TNM stage and tumor location was helpful for prognosis.

CONCLUSIONS

TNM stage and tumor location were independently prognostic in Chinese patients with resected SCLCs. Patient stratification by tumor location should inform the therapeutic strategy. The role of surgical resection for limited-stage SCLC patients must be reevaluated, as this may be appropriate for some patients.

The Addition of Peripheral Blood Inflammatory Indexes to Nomogram Improves the Predictive Accuracy of Survival in Limited-Stage Small Cell Lung Cancer Patients

Background

Accumulated evidence for systemic inflammation response in several solid tumors prompts a possibility of prediction of patients’ prognosis in a more accessible and valuable manner. However, the prognostic value of peripheral blood inflammatory markers in limited-stage small cell lung cancer (LS-SCLC) remains unclear. Therefore, we investigated the prognostic values of pretreatment inflammatory indexes in LS-SCLC patients.

Methods

We retrospectively identified 334 patients with LS-SCLC and collected their pretreatment serum levels of neutrophil, platelet, lymphocyte, leukocyte, hemoglobin, and albumin, then neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic inflammation index (SII) were calculated. Patients were dichotomized as low-Risk or high-Risk group based on their corresponding cutoff values. Univariate and multivariate analyses were conducted with a Cox proportional hazards model. The least absolute shrinkage and selection operator (LASSO)-Cox regression analysis was performed to construct the inflammation-related prognostic scoring system named Risk for OS. Nomograms were established to provide prognostic information, allowing for more individualized prediction of survival.

Results

Higher pretreatment platelet, lymphocyte, and albumin were indicators of favorable overall survival (OS), whereas higher NLR and SII were accompanied by inferior OS. The prognosis of patients with high Risk was significantly worse than that with low Risk in both the training group and the validation group (both p < 0.001). Comparable area under the curve (AUC) values between the training group and the validation group were observed, yielding 1-, 3-, and 5-year OS rates of 67.3% vs. 69.2%, 66.8% vs. 69.5%, and 66.7% vs. 71.4%, respectively. Multivariate analyses revealed that Risk [hazard ratio (HR) = 0.551, p < 0.001] was an independent negative prognostic indicator for OS, which was further verified in the validation set. The addition of Risk to nomogram (C-index = 0.643) harbored improved predictive accuracy for OS when compared with that of clinical factors alone (C-index = 0.606); the AUC values of 1-, 3-, and 5-year OS rates were 71.7% vs. 66.4%, 73.5% vs. 66.6%, and 71.9% vs. 65.6%, respectively.

Conclusions

Pretreatment peripheral blood inflammatory indexes may be a noninvasive serum biomarker for poor prognosis in LS-SCLC. The addition of Risk to the nomogram model could serve as a more powerful, economical, and practical method to predict survival for patients with LS-SCLC.

Neutrophil in the Pancreatic Tumor Microenvironment

Pancreatic ductal adenocarcinoma (PDAC) is a malignancy with a poor prognosis and low survival rates. PDAC is characterized by a fibroinflammatory tumor microenvironment enriched by abundant fibroblasts and a variety of immune cells, contributing to its aggressiveness. Neutrophils are essential infiltrating immune cells in the PDAC microenvironment. Recent studies have identified several cellular mechanisms by which neutrophils are recruited to tumor lesion and promote tumorigenesis. This review summarizes the current understanding of the interplay between neutrophils, tumor cells, and other components in the PDAC tumor microenvironment. The prognosis and therapeutic implications of neutrophils in PDAC are also discussed.