Can the prognosis of individual patients with nasopharyngeal carcinoma be predicted using a routine blood test at admission?

The prognostic value of pretreatment 18F-FDG PET-CT parameters with peripheral blood markers in patients with de novo metastatic nasopharyngeal carcinoma

BACKGROUND AND PURPOSE

To develop and validate a prognostic nomogram based on pretreatment 18F-fluorodeoxyglucose positron emission tomography/computed tomography (PET-CT)radiomics parameters and peripheral blood markers for risk stratification in patients with de novo metastatic nasopharyngeal carcinoma (dmNPC).

MATERIALS AND METHODS

A total of 558 patients with dmNPC were retrospectively enrolled between 2011 and 2019. Eligible patients were randomly divided into training and validation cohorts (7:3 ratio). A Cox regression model was used to identify prognostic factors for overall survival (OS). The predictive accuracy and discriminative ability of the prognostic nomogram were determined using the concordance index (C-index) and calibration curve.

RESULTS

Independent factors derived from multivariable analysis of the training cohort to predict death were lactate dehydrogenase levels, pretreatment Epstein-Barr virus DNA, total lesion glycolysis of locoregional lesions, number of metastatic lesions, and age, all of which were assembled into a nomogram with (nomogram B) or without PET-CT parameters (nomogram A). The C-index of nomogram B for predicting death was 0.70, which was significantly higher than the C-index values for nomogram A. Patients were then stratified into low- and high-risk groups based on the scores calculated using nomogram B for OS. The median OS was significantly higher in the low-risk group than in the high-risk group (69.60 months [95 % CI: 58.50-108.66] vs. 21.40 months [95 % CI: 19.20-23.90]; p＜0.01). All the results were confirmed in the validation cohort.

CONCLUSION

The proposed nomogram including PET-CT parameters yielded accurate prognostic predictions for patients with dmNPC, enabling effective risk stratification for these patients.

Individualized radiology screening for newly diagnosed nasopharyngeal carcinoma

OBJECTIVES

Current guidelines recommend universal PET/CT screening for metastases staging in newly diagnosed nasopharyngeal carcinoma (NPC) despite the low rate of synchronous distant metastasis (SDM). The study aims to achieve individualized screening recommendations of NPC based on the risk of SDM.

METHODS AND MATERIALS

18 pre-treatment peripheral blood indicators was retrospectively collected from 2271 primary NPC patients. A peripheral blood risk score (PBRS) was constructed by indicators associated with SDM on least absolute shrinkage and selection operator (LASSO) regression. The PBRS-based distant metastases (PBDM) model was developed from features selected by logistic regression analyses in the training cohort and then validated in the validation cohort. Receiver operator characteristic curve analysis, calibration curves, and decision curve analysis were applied to evaluate PBDM model performance.

RESULTS

Pre-treatment Epstein-Barr viral DNA copy number, percentage of total lymphocytes, serum lactate dehydrogenase level, and monocyte-to-lymphocyte ratio were most strongly associated with SDM in NPC and used to construct the PBRS. Sex (male), T stage (T3-4), N stage (N2-3), and PBRS (≥1.076) were identified as independent risk factors for SDM and applied in the PBDM model, which showed good performance. Through the model, patients in the training cohort were stratified into low-, medium-, and high-risk groups. Individualized screening recommendations were then developed for patients with differing risk levels.

CONCLUSION

The PBDM model offers individualized recommendations for applying PET/CT for metastases staging in NPC, allowing more targeted screening of patients with greater risk of SDM compared with current recommendations.

Cost-effective prognostic evaluation of breast cancer: using a STAR nomogram model based on routine blood tests

Background

Breast cancer (BC) is the most common and prominent deadly disease among women. Predicting BC survival mainly relies on TNM staging, molecular profiling and imaging, hampered by subjectivity and expenses. This study aimed to establish an economical and reliable model using the most common preoperative routine blood tests (RT) data for survival and surveillance strategy management.

Methods

We examined 2863 BC patients, dividing them into training and validation cohorts (7:3). We collected demographic features, pathomics characteristics and preoperative 24-item RT data. BC risk factors were identified through Cox regression, and a predictive nomogram was established. Its performance was assessed using C-index, area under curves (AUC), calibration curve and decision curve analysis. Kaplan-Meier curves stratified patients into different risk groups. We further compared the STAR model (utilizing HE and RT methodologies) with alternative nomograms grounded in molecular profiling (employing second-generation short-read sequencing methodologies) and imaging (utilizing PET-CT methodologies).

Results

The STAR nomogram, incorporating subtype, TNM stage, age and preoperative RT data (LYM, LYM%, EOSO%, RDW-SD, P-LCR), achieved a C-index of 0.828 in the training cohort and impressive AUCs (0.847, 0.823 and 0.780) for 3-, 5- and 7-year OS rates, outperforming other nomograms. The validation cohort showed similar impressive results. The nomogram calculates a patient's total score by assigning values to each risk factor, higher scores indicating a poor prognosis. STAR promises potential cost savings by enabling less intensive surveillance in around 90% of BC patients. Compared to nomograms based on molecular profiling and imaging, STAR presents a more cost-effective, with potential savings of approximately $700-800 per breast cancer patient.

Conclusion

Combining appropriate RT parameters, STAR nomogram could help in the detection of patient anemia, coagulation function, inflammation and immune status. Practical implementation of the STAR nomogram in a clinical setting is feasible, and its potential clinical impact lies in its ability to provide an early, economical and reliable tool for survival prediction and surveillance strategy management. However, our model still has limitations and requires external data validation. In subsequent studies, we plan to mitigate the potential impact on model robustness by further updating and adjusting the data and model.

Prognostic Factors and Construction of Nomogram Prediction Model of Lung Cancer Patients Using Clinical and Blood Laboratory Parameters

Objective

This work aimed to explore the prognostic risk factors of lung cancer (LC) patients and establish a line chart prediction model.

Methods

A total of 322 LC patients were taken as the study subjects. They were randomly divided into a training set (n = 202) and a validation set (n = 120). Basic information and laboratory indicators were collected, and the progression-free survival (PFS) and overall survival (OS) were followed up. Single-factor and cyclooxygenase (COX) multivariate analyses were performed on the training set to construct a Nomogram prediction model, which was validated with 120 patients in the validation set, and Harrell's consistency was analyzed.

Results

Single-factor analysis revealed significant differences in PFS (P<0.05) between genders, body mass index (BMI), carcinoembryonic antigen (CEA), cancer antigen 125 (CA125), squamous cell carcinoma antigen (SCCA), treatment methods, treatment response evaluation, smoking status, presence of pericardial effusion, and programmed death ligand 1 (PD-L1) at 0 and 1-50%. Significant differences in OS (P<0.05) were observed for age, tumor location, treatment methods, White blood cells (WBC), uric acid (UA), CA125, pro-gastrin-releasing peptide (ProGRP), SCCA, cytokeratin fragment 21 (CYFRA21), and smoking status. COX analysis identified male gender, progressive disease (PD) as treatment response, and SCCA > 1.6 as risk factors for LC PFS. The consistency indices of the line chart models for predicting PFS and OS were 0.782 and 0.772, respectively.

Conclusion

Male gender, treatment response of PD, and SCCA > 1.6 are independent risk factors affecting the survival of LC patients. The PFS line chart model demonstrates good concordance.

Nutritional Status and Incidence of Radiation-Induced Oral Mucositis in Nasopharyngeal Carcinoma Patients Treated with Chemoradiotherapy

Malnutrition is prevalent among patients with nasopharyngeal carcinoma undergoing radiotherapy. This study examined the nutritional status and incidence of radiation-induced oral mucositis (RIOM) in patients with nasopharyngeal carcinoma. A retrospective analysis was conducted to compare the incidence of RIOM, Nutritional Risk Screening (NRS) 2002 score, weight, body mass index (BMI), and hemoglobin levels in 338 patients treated with induction chemotherapy (IC) plus concurrent chemoradiotherapy (CCRT) or treated with CCRT alone. The IC + CCRT group exhibited an increase in weight and BMI but a decrease in hemoglobin levels after IC compared with baseline (p < 0.001). Both groups showed differences in weight at Week 0 and BMI at Weeks 0-2 of radiotherapy (p < 0.05). The IC + CCRT group experienced an increase in NRS 2002 scores from Week 2 to Week 6 (p < 0.05). The hemoglobin levels of the IC + CCRT group were consistently lower throughout radiotherapy (p < 0.001). However, no significant difference was observed in the incidence of RIOM between the two groups (p = 0.246). Patients treated with IC + CCRT exhibited a higher nutritional risk during radiotherapy. Although the incidence of Grade III RIOM was high, no significant difference was found between the groups.

Prognostic nutritional index and serum lactate dehydrogenase predict the prognosis of nasopharyngeal carcinoma patients who received intensity-modulated radiation therapy

PURPOSE

This research aimed to evaluate the prognostic significance of baseline prognostic nutritional index (PNI) and lactate dehydrogenase (LDH) for the outcome of individuals diagnosed with non-metastatic nasopharyngeal carcinoma (NPC).

METHODS

A retrospective analysis was conducted on data from 810 patients with non-metastatic NPC who underwent intensity-modulated radiation therapy (IMRT) with or without chemotherapy. The best cut-offs for PNI and LDH were identified by X-tile software to be 48.5 and 150, respectively. To find the independent prognostic factors for survival outcomes, univariate and multivariate regression analyses were conducted, and AUCs were used to compare their prognostic values.

RESULTS

Multivariate analysis revealed that patients with PNI > 48.5 had better overall survival (OS) (HR: 0.502, P < 0.001), progression-free survival (PFS) (HR: 0.618, P < 0.001), and distant metastasis-free survival (DMFS) (HR: 0.637, P = 0.005). Higher LDH was associated with poorer OS (HR: 1.798, P < 0.001), PFS (HR: 1.671, P < 0.001), and DMFS (HR: 1.756, P < 0.001). The combination of low PNI and high LDH in non-metastatic NPC patients was correlated with poor OS (P < 0.001), PFS (P < 0.001), and DMFS (P < 0.001). The combination of PNI and LDH had the highest AUCs for predicting OS, PFS, and DMFS.

CONCLUSIONS

PNI and LDH might become valuable predictors of the prognosis of non-metastatic NPC patients undergoing IMRT with or without chemotherapy. Prognostic accuracy can be enhanced by combining PNI and LDH.

A Novel Prognostic Model Predicts Outcomes in Non-Metastatic Nasopharyngeal Carcinoma Based on Inflammation, Nutrition, and Coagulation Signature

Purpose

This study aimed to assess the prognostic and predictive value of a circulating hematological signature (CHS) and to develop a CHS-based nomogram for predicting prognosis and guiding individualized chemotherapy in non-metastatic nasopharyngeal carcinoma (NPC) patients.

Patients and Methods

NPC patients were recruited between January 2014 and December 2017 at the Jiangxi Cancer Hospital. The CHS was constructed based on a series of hematological indicators. The nomogram was developed by CHS and clinical factors.

Results

A total of 779 patients were included. Three biomarkers were selected by least absolute shrinkage and selection operator regression, including prognostic nutritional index, albumin-to-fibrinogen ratio, and prealbumin-to-fibrinogen ratio, were used to construct the CHS. The patients in the low-CHS group had better 5-year DMFS and OS than those in the high-CHS group in the training (DMFS: 85.0% vs 56.6%, p<0.001; OS: 90.3% vs 65.4%, p<0.001) and validation cohorts (DMFS: 92.3% vs 43.6%, p<0.001; OS: 92.1% vs 65.5%, p<0.001). The nomogram_CHS showed better performance than clinical stage in predicting distant metastasis (concordance index: 0.728 vs 0.646). In the low-TRS (total risk scores) group, the patients received RT alone, CCRT and IC plus CCRT had similar 5-year DMFS and OS (p>0.05). In the middle-TRS group, the patients received RT alone had worse 5-year DMFS (58.7% vs 80.8% vs 90.8%, p=0.002) and OS (75.0% vs 94.1% vs 95.0%, p=0.001) than those received CCRT or IC plus CCRT. In the high-TRS group, the patients received RT alone and CCRT had worse 5-year DMFS (18.6% vs 31.3% vs 81.5%, p<0.001) and OS (26.9% vs 53.2% vs 88.8%, p<0.001) than those received IC plus CCRT.

Conclusion

The developed nomogram_CHS had satisfactory prognostic accuracy in NPC patients and may individualize risk estimation to facilitate the identification of suitable IC candidates.