Prognostic value of preoperative lymphocyte-to-monocyte ratio in oral cancer patients and establishment of a dynamic nomogram

Prognostic value of pretreatment lymphocyte percentage in oral cancer: A prospective cohort study

OBJECTIVE

To assess the prognostic role of pretreatment lymphocyte percentage (LY%) for patients with oral squamous cell carcinoma (OSCC).

METHODS

A large-scale prospective cohort study between July 2002 and March 2021 was conducted. Propensity score-matched (PSM) analysis and inverse probability of treatment weighting (IPTW) analysis were performed to adjust for potential confounders. Using random survival forest (RSF), the relative importance of pretreatment LY% in prognosis prediction was also assessed.

RESULTS

A total of 743 patients were enrolled and followed up (median: 2.75 years, interquartile range: 1.25-4.42 years). A high pretreatment LY% was significantly associated with better disease-specific survival of patients with OSCC (Hazard ratio [HR] = 0.60, 95% confidence interval [CI]: 0.42, 0.84). The same tendency was observed in PSM (HR = 0.57, 95% CI: 0.38, 0.85) and IPTW analysis (HR = 0.57, 95% CI: 0.40, 0.82). RSF showed that LY% ranked the fifth among importance ranking of all prognostic factors.

CONCLUSION

Pretreatment LY% showed a moderate predictive ability, suggesting it might be a valuable tool to predict prognosis for patients with OSCC.

The development and external validation of a web-based nomogram for predicting overall survival with Ewing sarcoma in children

Background

Ewing sarcoma remains the second most prevalent primary aggressive bone tumor in teens and young adults. The aim of our study was to develop and validate a web-based nomogram to predict the overall survival for Ewing sarcoma in children.

Methods

A total of 698 patients, with 640 cases from the Surveillance, Epidemiology, and End Results (the training set) and 58 cases (the external validation set), were included in this study. Cox analyses were carried out to determine the independent prognostic indicators, which were further included to establish a web-based nomogram. The predictive abilities were tested through the concordance index, calibration curve, decision curve analysis, and area under the receiver operating characteristic curve.

Results

As suggested by univariate and multivariate Cox analyses, age, primary site, tumor size, metastasis stage (M stage), and chemotherapy were included as the independent predictive variables. The area under the receiver operating characteristic curve values, calibration curves, concordance index, and decision curve analysis from training and validation groups suggested the model has great clinical applications.

Conclusion

We developed a convenient and precise web-based nomogram to evaluate overall survival for Ewing sarcoma in children. The application of this nomogram would assist physicians and patients in making decisions.

Nomogram based on pretreatment hepatic and renal function indicators for survival prediction of locally advanced esophageal squamous cell carcinoma with treatment of neoadjuvant chemoradiotherapy plus surgery

The parameters for survival prediction of esophageal squamous cell carcinoma (ESCC) patients treated with neoadjuvant chemoradiotherapy (NCRT) combined with surgery are unclear. Here, we aimed to construct a nomogram for survival prediction of ESCC patients treated with NCRT combined with surgery based on pretreatment serological hepatic and renal function tests. A total of 174 patients diagnosed as ESCC were enrolled as a training cohort from July 2007 to June 2019, and approximately 50% of the cases (n = 88) were randomly selected as an internal validation cohort. Univariate and multivariate Cox survival analyses were performed to identify independent prognostic factors to establish a nomogram. Predictive accuracy of the nomogram was evaluated by Harrell's concordance index (C-index) and calibration curve. ALT, ALP, TBA, TP, AST, TBIL and CREA were identified as independent prognostic factors and incorporated into the construction of the hepatic and renal function test nomogram (HRFTNomogram). The C-index of the HRFTNomogram for overall survival (OS) was 0.764 (95% CI 0.701-0.827) in the training cohort, which was higher than that of the TNM staging system (0.507 (95% CI 0.429-0.585), P < 0.001). The 5-year OS calibration curve of the training cohort demonstrated that the predictive accuracy of the HRFTNomogram was satisfactory. Moreover, patients in the high-risk group stratified by the HRFTNomogram had poorer 5-year OS than those in the low-risk group in the training cohort (27.4% vs. 80.3%, P < 0.001). Similar results were observed in the internal validation cohort. A novel HRFTNomogram might help predict the survival of locally advanced ESCC patients treated with NCRT followed by esophagectomy.

Nomogram incorporating potent inflammatory indicators for overall survival estimation of patients with primary oral squamous cell carcinoma

Background

Inflammation has been recognized to be a factor that substantially influences tumorigenesis and tumor prognosis. Hence, this study was aimed to investigate an inflammatory marker with the most potent prognostic ability and to evaluate the survival estimation capability of dynamic change in this marker for patients suffered from oral squamous cell carcinoma (OSCC).

Methods

469 patients' inflammatory indicators including lymphocyte-to-monocyte ratio (LMR), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and systemic inflammatory response index (SIRI), were calculated. Their predictive abilities for overall survival (OS) were evaluated by Kaplan-Meier curves to screen for the one with the most potent prognostic value. The predictive ability of dynamic changes in this marker was verified and a predictive nomogram incorporating inflammatory indicators was developed.

Results

A high LMR was identified to be an indicator of a satisfactory survival rate. Compared with that of other inflammatory markers, area under the receiver operating characteristics (ROC) curve (AUC) of LMR for 1-year and 3-year OS was significantly larger (P<0.001). Dynamic LMR change remained an significant parameter for predicting OS (OR: 2.492, 95% CI: 1.246-4.981, p = 0.010). The nomogram incorporating LMR exhibited a superior prognostic significance than the TNM system, as suggested by the C-index (0.776 vs 0.651 in primary cohort; 0.800 vs 0.707 in validation cohort, P<0.001) and AUC.

Conclusions

LMR was demonstrated to possess a more potent survival estimation capability than the other three inflammatory parameters. Dynamic changes in LMR serves as a significant parameter for overall survival estimation of primary OSCC patients. The established nomogram incorporating inflammatory markers showed more accuracy and sensitivity for survival estimation of primary OSCC patients.

Prognostic and clinicopathological significance of prognostic nutritional index (PNI) in patients with oral cancer: a meta-analysis

Accumulating literature has explored how prognostically significant the prognostic nutritional index (PNI) was for the oral carcinoma population, but with inconsistent findings. Therefore, we retrieved the most recent data and carried out this meta-analysis to comprehensively analyze the prognostic performance of pretreatment PNI in oral cancer. The electronic databases of PubMed, Embase, China National Knowledge Infrastructure (CNKI), Cochrane Library and Web of Science were fully retrieved. PNI's prognostic value for survival outcomes in oral carcinoma was assessed by estimating pooled hazard ratios (HRs) plus 95% confidence intervals (CIs). We examined the correlation of PNI with clinicopathological traits of oral carcinoma by utilizing the pooled odds ratios (ORs) plus 95% CIs. According to the pooled results of the present meta-analysis, which enrolled 10 studies involving 3,130 patients, for oral carcinoma suffers whose PNI was low, their disease-free survival (DFS) (HR=1.92, 95%CI=1.53-2.42, p<0.001) and overall survival (OS) (HR=2.44, 95%CI=1.45-4.12, p=0.001) would be inferior. Nonetheless, cancer-specific survival (CSS) was not linked significantly to PNI for the oral carcinoma population (HR=1.89, 95%CI=0.61-5.84, p=0.267). Significant associations of low PNI with TNM stages III-IV (OR=2.16, 95%CI=1.60-2.91, p<0.001) and age ≥ 65 years (OR=2.29, 95%CI=1.76-2.98, p<0.001) were found. As suggested by the present meta-analysis, a low PNI was linked to inferior DFS and OS among oral carcinoma patients. Oral cancer patients with low PNI may have high-risk of tumor progression. PNI could be served as a promising and effective index to predict prognosis in patients with oral cancer.

Immune cell-lipoprotein imbalance as a marker for early diagnosis of non-small cell lung cancer metastasis

The underlying molecular mechanisms and evolutionary patterns of lung cancer metastasis remain unclear, resulting in a lack of effective indicators for early diagnosis of metastasis. We retrospectively analyzed 117 patients with primary non-small cell lung cancer (NSCLC) admitted to Tongji Hospital of Tongji University in 2021, of which 93 patients with tumor metastasis were set as the metastasis group. 24 patients without metastasis were set as the non-metastasis group. The differences of each index in the two groups of patients and the expression levels in different TNM stages were compared. This study intends to evaluate the diagnostic value and net clinical benefit of common blood-related indicators Neutrophil/lymphocyte (NLR), lymphocyte/monocyte (LMR), High density lipoprotein/neutrophil (HNR), High density lipoprotein/monocyte (HMR) and combined assays in NSCLC metastasis for the early diagnosis of patients with NSCLC metastasis. It was found that the level of NLR was higher in metastatic NSCLC than non-metastatic, but the level of LMR, HNR and HMR was lower. The levels of NLR, LMR, HNR and HMR in patients with different TNM stages showed that NLR levels increased with TNM stage, while LMR, HNR and HMR levels decreased. The threshold probability range of the 4 combined tests was greater and the overall clinical benefit rate was higher compared to the individual tests. Our findings suggest that NLR, LMR, HNR and HMR have better diagnostic value for NSCLC metastasis. This study provides a clinical basis for investigating the mechanisms by which immune cells and lipid metabolism-related proteins remodel the microenvironment prior to NSCLC metastasis.

A Novel Model Combining Tumor Length, Tumor Thickness, TNM_Stage, Nutritional Index, and Inflammatory Index Might Be Superior to the 8th TNM Staging Criteria in Predicting the Prognosis of Esophageal Squamous Cell Carcinoma Patients Treated With Definitive Chemoradiotherapy

Background

We aimed to determine whether the tumor length and tumor thickness should be used as prognostic factors for esophageal squamous cell carcinoma (ESCC) patients treated with definitive chemoradiotherapy (dCRT).

Methods

A retrospective analysis consists of 902 non-operative ESCC patients received dCRT. The nomogram was used to predict the survival. Besides, Restricted Cubic Splines (RCS) was used to examine the relationship between prognostic factors and survival outcomes. Finally, the prognostic index (PI) scores were constructed according to the tumor length and tumor thickness, and the patients were divided into the low-, medium-, and high-risk groups.

Results

The median follow-up of overall survival (OS) and progression-free survival (PFS) were 23.0 months and 17.5 months. Multivariate Cox regression analysis showed that tumor length and tumor thickness were independent prognostic factors associated with survival. Our novel nomograms for OS and PFS were superior to the TNM classification (p < 0.001). Besides, RCS analysis demonstrated that the death hazard of tumor length and tumor thickness sharply increased at 7.7 cm and 1.6 cm (p < 0.001). Finally, there were significant differences for ESCC patients with clinical TNM stage group of the OS and PFS in different risk groups. The higher risk group was significantly associated with shorter OS and PFS in ESCC patients (both p < 0.001 for all).

Conclusion

The study results suggest that the novel models integrating tumor length and tumor thickness may provide a simple and widely available method for evaluating the prognosis of non-operative ESCC patients. The tumor length and tumor thickness should be considered as prognostic factors for ESCC.

Utility of prognostic nutritional index and systemic immune-inflammation index in oral cancer treatment

PURPOSE

This study aimed to evaluate the utility of inflammation-based prognostic scores (IBPS) and systemic immune-inflammation index (SII) in the treatment of oral cancer patients.

METHODS

For the 183 patients enrolled in this study, IBPS and SII were calculated from peripheral blood samples obtained before and after treatment and at the time of relapse. We examined overall survival (OS) and disease-free survival (DFS) using previously reported cut-off values for IBPS. Cut-off values of neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR), and prognostic nutritional index (PNI) were analyzed as NLR 1.79, PLR 114.97, LMR 5, and PNI 52.44. The cut-off value for SII was set at 569. OS and DFS were analyzed by Kaplan-Meier methods using the cutoff of each IBPS and SII. Univariate analysis and multivariate analysis using Cox proportional hazards were performed for OS and DFS.

RESULTS

Kaplan-Meier methods showed the high-PNI group showed good prognosis including OS and DFS, while the high-SII group displayed poor DFS. Univariate analysis showed that pre-treatment high PNI and low SII were significantly associated with better prognosis. Multivariate analysis identified pre-treatment PNI as independently associated with OS. For DFS, univariate analysis using Cox proportional hazards modeling showed that pre-treatment high NLR and high SII were significantly associated with worse prognosis, while high PNI was significantly associated with better prognosis. Multivariate analysis identified pre-treatment PNI and SII as independently associated with DFS. Parameters of PNI and SII components were compared between pre-treatment, post-treatment and at relapse in the high- and low-PNI groups. PNI was predominantly decreased in both high- and low-PNI groups at post-treatment and at relapse compared to pre-treatment. This trend was also observed for albumin.

CONCLUSIONS

Higher pre-treatment PNI was associated with better OS, while lower pre-treatment PNI and higher treatment SII were associated with poorer DFS in oral cancer patients. Our data indicated that PNI and SII might offer useful biomarkers for gauging prognosis and the efficacy of conventional therapies.

An Externally Validated Dynamic Nomogram for Predicting Unfavorable Prognosis in Patients With Aneurysmal Subarachnoid Hemorrhage

Background: Aneurysmal subarachnoid hemorrhage (aSAH) leads to severe disability and functional dependence. However, no reliable method exists to predict the clinical prognosis after aSAH. Thus, this study aimed to develop a web-based dynamic nomogram to precisely evaluate the risk of poor outcomes in patients with aSAH.

Methods: Clinical patient data were retrospectively analyzed at two medical centers. One center with 126 patients was used to develop the model. Least absolute shrinkage and selection operator (LASSO) analysis was used to select the optimal variables. Multivariable logistic regression was applied to identify independent prognostic factors and construct a nomogram based on the selected variables. The C-index and Hosmer–Lemeshow p-value and Brier score was used to reflect the discrimination and calibration capacities of the model. Receiver operating characteristic curve and calibration curve (1,000 bootstrap resamples) were generated for internal validation, while another center with 84 patients was used to validate the model externally. Decision curve analysis (DCA) and clinical impact curves (CICs) were used to evaluate the clinical usefulness of the nomogram.

Results: Unfavorable prognosis was observed in 46 (37%) patients in the training cohort and 24 (29%) patients in the external validation cohort. The independent prognostic factors of the nomogram, including neutrophil-to-lymphocyte ratio (NLR) (p = 0.005), World Federation of Neurosurgical Societies (WFNS) grade (p = 0.002), and delayed cerebral ischemia (DCI) (p = 0.0003), were identified using LASSO and multivariable logistic regression. A dynamic nomogram (https://hu-ping.shinyapps.io/DynNomapp/) was developed. The nomogram model demonstrated excellent discrimination, with a bias-corrected C-index of 0.85, and calibration capacities (Hosmer–Lemeshow p-value, 0.412; Brier score, 0.12) in the training cohort. Application of the model to the external validation cohort yielded a C-index of 0.84 and a Brier score of 0.13. Both DCA and CIC showed a superior overall net benefit over the entire range of threshold probabilities.

Conclusion: This study identified that NLR on admission, WFNS grade, and DCI independently predicted unfavorable prognosis in patients with aSAH. These factors were used to develop a web-based dynamic nomogram application to calculate the precise probability of a poor patient outcome. This tool will benefit personalized treatment and patient management and help neurosurgeons make better clinical decisions.

Development and Validation of a Nomogram based on cell growth-related Biomarkers for Oral Squamous Cell Carcinoma

Purpose: We aimed to develop a prognostic nomogram based on immunohistochemistry (IHC) biomarkers of patients with oral squamous cell carcinoma (OSCC). Methods: A total of 294 patients were enrolled in the study. The least absolute shrinkage and selection operator (LASSO) Cox regression model was performed to develop a combined IHC score (IHCs) classifier. Results: Five biomarkers, specifically c-Met, Vimentin, HIF-2α, VEGF-c, and Bcl-2 were extracted. Then, an IHCs classifier was developed, and patients were stratified into high- and low-IHCs groups. In the training cohort, the 5-year overall survival (OS) was 62.1% in low-IHCs group and 28.2% in high-IHCs group (P<0.001). The 5-year OS was 68.6% for the low-IHCs group and 28.4% for the high-IHCs group in the validation cohort (P<0.001). The area under the ROC curve (AUROC) of the combination of the IHCs classifier and TNM stage was 0.746 (95% CI: 0.658-0.833) in the training cohort and 0.735 (95% CI: 0.651-0.818) in the validation cohort, respectively. Conclusions: The nomogram could effectively predict the prognosis for patients with OSCC and may be employed as a potential tool to guide the individual decision-making process.

A web-based dynamic Nomogram for predicting instrumental activities of daily living disability in older adults: a nationally representative survey in China

Background

Instrumental Activities of Daily Living (IADL) disability is a common health burden in aging populations. The identification of high-risk individuals is essential for timely targeted interventions. Although predictors for IADL disability have been well described, studies constructing prediction tools for IADL disability among older adults were not adequately explored. Our study aims to develop and validate a web-based dynamic nomogram for individualized IADL disability prediction in older adults.

Methods

Data were obtained from the China Health and Retirement Longitudinal Study (CHARLS). We included 4791 respondents aged 60 years and over, without IADL disability at baseline in the 2011 to 2013 cohort (training cohort) and 371 respondents in the 2013 to 2015 cohort (validation cohort). Here, we defined IADL disability as needing any help in any items of the Lawton and Brody’s scale. A web-based dynamic nomogram was built based on a logistic regression model in the training cohort. We validated the nomogram internally with 1000 bootstrap resamples and externally in the validation cohort. The discrimination and calibration ability of the nomogram was assessed using the concordance index (C-index) and calibration plots, respectively.

Results

The nomogram incorporated ten predictors, including age, education level, social activity frequency, drinking frequency, smoking frequency, comorbidity condition, self-report health condition, gait speed, cognitive function, and depressive symptoms. The C-index values in the training and validation cohort were 0.715 (bootstrap-corrected C-index = 0.702) and 0.737, respectively. The internal and external calibration plots for predictions of IADL disability were in excellent agreement. An online web server was built (https://lilizhang.shinyapps.io/DynNomapp/) to facilitate the use of the nomogram.

Conclusions

We developed a dynamic nomogram to evaluate the risk of IADL disability precisely and expediently. The application of this nomogram would be helpful for health care physicians in decision-making.