The Positive Lymph Node Ratio Predicts Survival in T1-4N1-3M0 Non-Small Cell Lung Cancer: A Nomogram Using the SEER Database

Association between neutrophil to high-density lipoprotein cholesterol ratio and disease severity in patients with acute biliary pancreatitis

BACKGROUND

The neutrophil to high-density lipoprotein cholesterol ratio (NHR) is independently associated with the severity of various diseases. However, its association with acute biliary pancreatitis (ABP) remains unknown.

METHODS

This study included 1335 eligible patients diagnosed with ABP from April 2016 to December 2022. Patients were divided into low- and high-NHR level groups using an optimal cut-off value determined utilizing Youden's index. Multivariate logistic regression analysis was used to investigate the correlation between NHR and ABP severity. Multivariate analysis-based limited restricted cubic spline (RCS) method was used to evaluate the nonlinear relationship between NHR and the risk of developing moderate or severe ABP.

RESULTS

In this study, multivariate logistic regression analysis indicated an independent association between NHR and ABP severity (p < .001). The RCS analysis showed a linear correlation between NHR and the risk of developing moderate or severe ABP (P for non-linearity > 0.05), and increased NHR was found to be independently associated with a more severe form of the disease.

CONCLUSIONS

Our study suggests that NHR is a simple and practical independent indicator of disease severity, serving as a potential novel predictor for patients with ABP.

Prognostic Value of Lymph Node Ratio (LNR) in Patients with Postoperative N2 Feature in Non-Small Cell Lung Cancer (NSCLC)

Introduction: One of the most important prognostic factors in non-small cell lung cancer (NSCLC), a condition with a high mortality rate, is the presence of mediastinal lymph node metastases alongside distant metastases. The aim of this study was to evaluate the prognostic value of selected parameters of N2 stage NSCLC with a special focus on lymph node ratio (LNR). Material: The study included 163 patients (61 women and 102 men) operated on due to NSCLC, postoperatively diagnosed as stage N2. The age of the patients ranged from 38 to 82 years (mean age: 62.4 years). The effects of the following factors on clinical data and survival rate were assessed: N1 stage, total number of all metastatic nodes, LNR and LNR N2 ratios, and the presence of skip, single- or multistation metastases. Results: Univariate analysis showed patient survival to be correlated with LNR and LNR N2 ratios, single/multistation metastases, and the number of nodes involved in metastasis. A multivariate model based on patient clinical data found nicotine dependence (p = 0.013), LNR > 0.26 (p = 0.004), and Charlson Comorbidity Index (CCI) value > 3 (p = 0.014) to be independent adverse prognostic factors in this group. Conclusions: LNR ratio is a significant cancer disease-derived independent prognostic factor for patients with postoperative N2 stage NSCLC. In addition, smoking and comorbidities also appear to have prognostic value.

Prognostic value of the advanced lung cancer inflammation index in patients with gastric cancer after radical gastrectomy: a propensity-score matching cohort study and meta-analysis

BACKGROUND

Insufficient evidence existed about the prognostic role of the advanced lung cancer inflammation index (ALI) for gastric cancer patients who underwent curative resection. The aim of this study was to identify the predictive ability of ALI for survival after curative gastrectomy.

METHODS

We retrospectively analyzed 328 gastric cancer patients who received curative gastrectomy from the database of Chongqing University Cancer Hospital, and investigated the prognostic role of the preoperative ALI compared with clinicopathological variables and other serum biomarkers, such as preoperative neutrophil-to-lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR) and Lymphocyte-monocyte ratio (LMR). To minimize intergroup differences, propensity score matching (PSM) analysis was employed. Additionally, we performed a meta-analysis of four cohort studies published up to October 2023 following the PRISMA guidelines.

RESULTS

In the overall cohort, patients in the low ALI group had a significantly worse overall survival compared to those in the high ALI group (P < 0.0001). Subgroup analysis identified that ALI maintained its prognostic significance across different subgroups. In addition, ROC analysis showed that ALI had a higher AUC value for 3-year overall survival compared to NLR, PLR, and LMR (0.576 vs. 0.573 vs. 0.557 vs. 0.557). Multivariate analysis indicated that ALI, other than other serum biomarkers, was an independent risk factor for decreased overall survival in GC patients following curative surgery (HR = 1.449; 95%CI: 1.028-2.045; P = 0.034). Consistently, PSM analysis supported all of these findings. The meta-analysis including 4 studies evaluating 2542 patients, confirmed the association between the low ALI and poor survival outcomes.

CONCLUSION

The preoperative ALI was an independent prognostic factor for survival in gastric cancer patients who underwent curative gastrectomy.

Impact of the Alberta Stroke Program CT Score subregions on long-term functional outcomes in acute ischemic stroke: Results from two multicenter studies in China

Background and Objectives

The Alberta Stroke Program CT Score (ASPECTS) is a widely used rating system for assessing infarct extent and location. We aimed to investigate the prognostic value of ASPECTS subregions' involvement in the long-term functional outcomes of acute ischemic stroke (AIS).

Materials and Methods

Consecutive patients with AIS and anterior circulation large-vessel stenosis and occlusion between January 2019 and December 2020 were included. The ASPECTS score and subregion involvement for each patient was assessed using posttreatment magnetic resonance diffusion-weighted imaging. Univariate and multivariable regression analyses were conducted to identify subregions related to 3-month poor functional outcome (modified Rankin Scale scores, 3-6) in the reperfusion and medical therapy cohorts, respectively. In addition, prognostic efficiency between the region-based ASPECTS and ASPECTS score methods were compared using receiver operating characteristic curves and DeLong's test.

Results

A total of 365 patients (median age, 64 years; 70% men) were included, of whom 169 had poor outcomes. In the reperfusion therapy cohort, multivariable regression analyses revealed that the involvement of the left M4 cortical region in left-hemisphere stroke (adjusted odds ratio [aOR] 5.39, 95% confidence interval [CI] 1.53-19.02) and the involvement of the right M3 cortical region in right-hemisphere stroke (aOR 4.21, 95% CI 1.05-16.78) were independently associated with poor functional outcomes. In the medical therapy cohort, left-hemisphere stroke with left M5 cortical region (aOR 2.87, 95% CI 1.08-7.59) and caudate nucleus (aOR 3.14, 95% CI 1.00-9.85) involved and right-hemisphere stroke with right M3 cortical region (aOR 4.15, 95% CI 1.29-8.18) and internal capsule (aOR 3.94, 95% CI 1.22-12.78) affected were related to the increased risks of poststroke disability. In addition, region-based ASPECTS significantly improved the prognostic efficiency compared with the conventional ASPECTS score method.

Conclusion

The involvement of specific ASPECTS subregions depending on the affected hemisphere was associated with worse functional outcomes 3 months after stroke, and the critical subregion distribution varied by clinical management. Therefore, region-based ASPECTS could provide additional value in guiding individual decision making and neurological recovery in patients with AIS.

The influence of psychological resilience and nursing practice environment on nurses' moral courage: A cross-sectional study

AIM

To determine the relationship between psychological resilience, nursing practice environment, and moral courage of clinical nurses and also the factors influencing moral courage.

DESIGN

Cross-sectional study.

METHODS

586 nurses from a general hospital were selected by convenience sampling method in January 2023. The general information questionnaire, Nurses' Moral Courage Scale (NMCS), Resilience Scale, and Practice Environment Scale (PES) were measured. Hierarchical linear regression analysis was used to explore the influencing factors of clinical nurses' moral courage.

RESULTS

Nurses' average moral courage score was 79.00 (69.00, 91.00). The nurses' moral courage was positively correlated with psychological resilience and nursing practice environment. Multivariate linear regression analysis showed that psychological resilience and nursing practice environment entered the regression equation, accounting for 23.4% of the total variation. Psychological resilience and nursing practice environment are the main factors affecting the moral courage of clinical nurses. Nursing managers should conduct moral courage training, develop a decent nursing practice environment, pay attention to the psychological emotions of nurses, and actively build a safe, open, and supportive atmosphere for moral behaviour.

Association of serum occludin levels and perihematomal edema volumes in intracranial hemorrhage patients

BACKGROUND AND PURPOSE

Perihematomal edema (PHE) is one of the severe secondary damages following intracranial hemorrhage (ICH). Studies showed that blood-brain barrier (BBB) injury contributes to the development of PHE. Previous studies showed that occludin protein is a potential biomarker of BBB injury. In the present study, we investigated whether the levels of serum occludin on admission are associated with PHE volumes in ICH patients.

METHODS

This cross-sectional study included 90ICH patients and 32 healthy controls.The volumes of hematoma and PHE were assessed using non-contrast cranial CT within 30 min of admission. Blood samples were drawn on admission, and the levels of baseline serum occludin were detected using enzyme-linked immunosorbent assay. Partial correlation analysis and multiple linear regression analysis were performed to evaluate the association between serum occludin levels and PHE volumes in ICH patients.

RESULTS

The serum occludin levels in ICH patients were much higher than health controls (median 0.27 vs. 0.13 ng/mL, p < 0.001). At admission, 34 ICH patients (37.78%) had experienced a severe PHE (≥30 mL), and their serum occludin levels were higher compared to those with mild PHE (<30 mL) (0.78 vs. 0.21 ng/mL, p < 0.001). The area under the receiver operating characteristics curve (ROC) of serum occludin level in predicting severe PHE was 0.747 (95% confidence interval CI 0.644-0.832, p < 0.001). There was a significant positive correlation between serum occludin levels and PHE volumes (partial correlation r = 0.675, p < 0.001). Multiple linear regression analysis showed that serum occludin levels remained independently associated with the PHE volumes after adjusting other confounding factors.

CONCLUSION

The present study showed that serum occludin levels at admission were independently correlated with PHE volumes in ICH patients, which may provide a biomarker indicating PHE volume change.

Analysis of the diagnostic and prognostic value of serum PAD2 in patients with sepsis in the intensive care unit

BACKGROUND

Sepsis is a common disease in the intensive care unit (ICU). In recent years, the incidence rate and mortality rate remain high. Early diagnosis of sepsis is crucial for treatment and can effectively reduce mortality. So far, the ability of serum peptidylarginine deaminase 2 (PAD2) in the diagnosis and prognosis of sepsis patients is still unclear. We conducted this study to reveal the clinical value of PAD2 as a biomarker for sepsis patients.

METHODS

A prospective study method was used to select 207 patients in the ICU of Renmin Hospital of Wuhan University from May 2022 to May 2023. They were divided into the sepsis group (n = 135) and control group (n = 72), and data were collected within 24 h of hospitalization. Sepsis patients were divided into a survival group (n = 80) and a non-survival group (n = 55) based on their 28-day survival status. Using statistical methods to evaluate the diagnostic and prognostic value of PAD2 in sepsis.

RESULTS

The serum PAD2 concentrations in the sepsis group were significantly higher than in the control group (median 16.70 vs 35.32 ng/ml, P < 0.001). Multivariate logistic regression analysis showed that the Quick Sequential Organ Failure Assessment (qSOFA), C-reactive protein (CRP), procalcitonin (PCT), and PAD2 were independent risk factors for sepsis. The Receiver operating characteristic (ROC) curve showed that the combined diagnostic value of qSOFA, CRP, PCT, and PAD2 was the highest. The serum PAD2 concentrations in the non-survival group of patients with sepsis were significantly higher than those in the survival group (median 29.26 vs 50.08 ng/ml, P < 0.05). The COX regression analysis showed that PAD2, sequential organ failure score Assessment (SOFA) score, and Acute Physiology and Chronic Health Evaluation (APACHE II) score were independent factors affecting the prognosis of sepsis patients. The ROC analysis showed that the combined prognostic value of PAD2, SOFA, and APACHE II scores was significantly higher than any single indicator. The Kaplan-Meier survival analysis showed that patients with PAD2 ≤ 48.62 ng/ml had a better prognosis.

CONCLUSION

The significant increase in serum PAD2 concentrations in patients is an independent risk factor affecting the occurrence of sepsis and 28-day mortality. The combination of PAD2 and other indicators can further improve the diagnostic and prognostic value for ICU sepsis patients.

Association of radioactive iodine treatment in differentiated thyroid cancer and cardiovascular death: a large population-based study

PURPOSE

The risk of cardiovascular diseases' death (CVD) in patients with differentiated thyroid cancer (DTC) treated with radioactive iodine (RAI) after surgery has not been adequately studied.

METHODS

Data of DTC patients who received RAI after surgery were retrieved from the Surveillance, Epidemiology, and End Result (SEER) database (2004-2015). Standardized mortality rate (SMR) analysis was used to evaluate the CVD risk in patients with RAI vs general population. A 1:1 propensity score matching (PSM) was applied to balance inter-group bias, and Pearson's correlation coefficient was used to detect collinearity between variables. The Cox proportional hazard model and multivariate competing risk model were utilized to evaluate the impact of RAI on CVD. At last, we curved forest plots to compare differences in factors significantly associated with CVD or cancer-related deaths.

RESULTS

DTC patients with RAI treatment showed lower SMR for CVD than general population (RAI: SMR = 0.66, 95% CI 0.62-0.71, P < 0.05). After PSM, Cox proportional hazard regression demonstrated a decreased risk of CVD among patients with RAI compared to patients without (HR = 0.76, 95% CI 0.6-0.97, P = 0.029). However, in competing risk regression analysis, there was no significant difference (adjusted HR = 0.82, 95% CI 0.66-1.01, P = 0.11). The independent risk factors associated with CVD were different from those associated with cancer-related deaths.

CONCLUSION

The CVD risk between DTC patients treated with RAI and those who did not was no statistical difference. Noteworthy, they had decreased CVD risk compared with the general population.

A Nomogram for Predicting Survival in Advanced Non-Small-Cell Lung Carcinoma Patients: A Population-Based Study

Non-small-cell lung cancer (NSCLC) remains the most common malignant cancer. We identified 43140 advanced NSCLC patients from the SEER database to develop and validate a new prognostic model. The prognostic performance was evaluated by P value, concordance index, net reclassification index, integrated discrimination improvement, and decision curve analysis. The following variables were contained in the final prognostic model: age, sex, race, TNM stage, and grade and treatment options. Compared to the AJCC staging system, this prognostic model is conducive to the implementation of individualized clinical treatment schemes and can be an important part of the precise medical care of NSCLC tumors.

What factors are associated with the prognosis of primary testicular diffuse large B-cell lymphoma? A study based on the SEER database

PURPOSE

Primary testicular diffuse large B-cell lymphoma (PT-DLBCL) is a relatively rare urological tumor with a high degree of malignancy and a poor prognosis. This study aimed to investigate the prognostic risk factors for survival of patients with PT-DLBCL, and then to construct a predictive model and verify its reliability.

METHODS

First, we selected subjects from the SEER database (2000-2018) and analyzed the survival of PT-DLBCL patients by Kaplan-Meier test. Then, we analyzed prognostic factors by Cox regression. Finally, the data from the training cohort were used to construct a prediction model and represented with a nomogram. We evaluated the nomogram using the consistency index (C-index), decision curve analysis (DCA), and the area under the subject operating characteristic curve (ROC). In addition, calibration curves were plotted to assess the agreement between the column plot model and the actual model.

RESULTS

We identified five independent risk factors for patient prognosis affecting OS and CSS in patients with PT-DLBCL by univariate and multivariate analysis, including age, transversality, Ann Arbor staging, chemotherapy, and radiotherapy. According to the above factors, we constructed prognostic nomograms, and found that age contributed the most to the survival of patients with PT-DLBCL. The C-indexes for the nomogram of OS and CSS in the training cohort were 0.758 (0.716-0.799) and 0.763 (0.714-0.812), and in the validation cohort were OS and CSS 0.756 (0.697-0.815) and 0.748 (0.679-0.817).

CONCLUSION

We produced the first nomogram of PT-DLBCL, and it can be used to evaluate the CSS and OS of patients to determine the prognosis of patients.

Altered structural hippocampal intra-networks in a general elderly Japanese population with mild cognitive impairment

Although altered networks inside the hippocampus (hippocampal intra-networks) have been observed in dementia, the evaluation of hippocampal intra-networks using magnetic resonance imaging (MRI) is challenging. We employed conventional structural imaging and incident component analysis (ICA) to investigate the structural covariance of the hippocampal intra-networks. We aimed to assess altered hippocampal intra-networks in patients with mild cognitive impairment (MCI). A cross-sectional study of 2122 participants with 3T MRI (median age 69 years, 60.9% female) were divided into 218 patients with MCI and 1904 cognitively normal older adults (CNOA). By employing 3D T1-weighted imaging, voxels within the hippocampus were entered into the ICA analysis to extract the structural covariance intra-networks within the hippocampus. The ICA extracted 16 intra-networks from the hippocampal structural images, which were divided into two bilateral networks and 14 ipsilateral networks. Of the 16 intra-networks, two (one bilateral network and one ipsilateral networks) were significant predictors of MCI from the CNOA after adjusting for age, sex, education, disease history, and hippocampal volume/total intracranial volume ratio. In conclusion, we found that the relationship between hippocampal intra-networks and MCI was independent from the hippocampal volume. Our results suggest that altered hippocampal intra-networks may reflect a different pathology in MCI from that of brain atrophy.

Comparation between novel online models and the AJCC 8th TNM staging system in predicting cancer-specific and overall survival of small cell lung cancer

Background

Most of previous studies on predictive models for patients with small cell lung cancer (SCLC) were single institutional studies or showed relatively low Harrell concordance index (C-index) values. To build an optimal nomogram, we collected clinicopathological characteristics of SCLC patients from Surveillance, Epidemiology, and End Results (SEER) database.

Methods

24,055 samples with SCLC from 2010 to 2016 in the SEER database were analyzed. The samples were grouped into derivation cohort (n=20,075) and external validation cohort (n=3,980) based on America's different geographic regions. Cox regression analyses were used to construct nomograms predicting cancer-specific survival (CSS) and overall survival (OS) using derivation cohort. The nomograms were internally validated by bootstrapping technique and externally validated by calibration plots. C-index was computed to compare the accuracy and discrimination power of our nomograms with the 8th of version AJCC TNM staging system and nomograms built in previous studies. Decision curve analysis (DCA) was applied to explore whether the nomograms had better clinical efficiency than the 8th version of AJCC TNM staging system.

Results

Age, sex, race, marital status, primary site, differentiation, T classification, N classification, M classification, surgical type, lymph node ratio, radiotherapy, and chemotherapy were chosen as predictors of CSS and OS for SCLC by stepwise multivariable regression and were put into the nomograms. Internal and external validations confirmed the nomograms were accurate in prediction. C-indexes of the nomograms were relatively satisfactory in derivation cohort (CSS: 0.761, OS: 0.761) and external validation cohort (CSS: 0.764, OS: 0.764). The accuracy of the nomograms was superior to that of nomograms built in previous studies. DCA showed the nomograms conferred better clinical efficiency than 8th version of TNM staging system.

Conclusions

We developed practical nomograms for CSS (https://guowei2020.shinyapps.io/DynNom-CSS-SCLC/) and OS (https://drboidedwater.shinyapps.io/DynNom-OS-SCLC/) prediction of SCLC patients which may facilitate clinicians in individualized therapeutics.

Myeloid cell leukemia-1 as a candidate prognostic biomarker in cancers: a systematic review and meta-analysis

INTRODUCTION

Studies have shown that myeloma cell leukemia-1 (MCL-1) is associated with the prognosis of patients with cancer. To further validate the prognostic value of MCL-1 in cancer, a meta-analysis was conducted.

METHODS

Six databases were searched using Boolean logic search formulas. Data were extracted from the included literature, and pooled odds ratio, hazard ratio, and 95% confidence interval were calculated to determine the relationship between MCL-1 levels and clinicopathological characteristics and prognosis of patients with cancer. When heterogeneity was found to be significant, a random effects model was used, otherwise, a fixed effects model was used.

RESULTS

Twelve articles were included in this meta-analysis, totaling 2208 patients with cancer across 14 studies. A high MCL-1 expression level was associated with patients with high T stage, M stage, and TNM stage in some cancers. Additionally, high MCL-1 expression was likely to be observed in patients with poorly differentiated digestive system tumors and patients with lung adenocarcinoma. Notably, a higher expression of MCL-1 was found to be associated with shorter overall survival in patients with hematological tumors, digestive system tumors, and lung cancer.

CONCLUSION

MCL-1 may be a prognostic biomarker in patients with some types of cancer.

Prognostic significance of preoperative C-reactive protein to albumin ratio in non-small cell lung cancer patients: A meta-analysis

Objective

We aimed to assess whether C-reactive protein to albumin ratio (CAR) is associated with the clinicopathology and prognosis of patients with non-small cell lung cancer (NSCLC) after surgery.

Methods

Several literature databases were searched for eligible studies in English and Chinese published before September 1, 2022, according to the inclusion and exclusion criteria. The pooled odds ratios (ORs) with 95% confidence interval (CI) were calculated to assess the association of CAR in lung cancer with clinicopathological characteristics including age, sex, smoking status, lymph node metastasis, and American Association of Cancer (AJCC) stage. The pooled hazard ratios (HRs) with 95% CI were calculated to assess the association of CAR with prognosis in lung cancer. Publication bias was assessed using Egger's test.

Results

Overall, 9 studies involving 3,359 NSCLC patients were included in this meta-analysis. The CAR was observed to be higher in males, smokers, and patients with lymph node metastasis and correlated with advanced AJCC stage but not with age. Moreover, a high CAR correlated with poor survival. No publication bias was observed in this meta-analysis.

Conclusions

CAR was observed to be a significant biomarker for prognosis and associated with clinicopathological characteristics in patients with NSCLC after surgery.

Prognostic nutritional index: A potential biomarker for predicting the prognosis of decompensated liver cirrhosis

Background

Prognostic nutritional index (PNI) is an independent predictor of the prognosis of various diseases. However, the prognosis value of PNI in patients with decompensated liver cirrhosis (DLC) remains unknown. The study aimed to investigate the prognostic significance of PNI in patients with DLC.

Methods

A total of 214 eligible patients were enrolled in the study's development cohort between January 2018 and March 2021. The clinical primary study endpoints were mortality at 3 and 6 months. Receiver operating characteristic (ROC) curve analysis was used to assess the PNI's prediction accuracy, and Youden's index was utilized to determine the PNI's optimal cut-off value. Moreover, based on the optimal cut-off value, patients were categorized into high and low PNI groups. Multivariate logistic regression analysis was used to determine independent risk factors for mortality, while the relationship between PNI and the risk of death was identified and demonstrated using restricted cubic splines (RCS). A validation cohort of 139 patients was to verify the predictive power of the PNI.

Results

In the development cohort, the mortality rate at 3 and 6 months were 10.3% (22) and 14.0% (30), respectively. The PNI had comparable predictive power with the MELD score at all follow-up endpoints. Decreased PNI was an independent predictor of adverse prognosis at all follow-up endpoints. The RCS revealed a linear correlation between PNI and the risk of death. We confirmed that lower PNI was an independent predictor of poor prognosis in the validation cohort.

Conclusion

The findings showed that lower PNI is an independent factor of poor outcomes and might be utilized as a potentially promising prognostic predictor in patients with DLC.

A clinical nomogram based on absolute count of lymphocyte subsets for predicting overall survival in patients with non-small cell lung cancer

BACKGROUND

The absolute count of lymphocyte subsets (ACLS) is correlated to the prognosis of multiple malignancies. This study aimed to combine the ACLS with the clinicopathological parameters to develop a nomogram to accurately predict the prognosis of non-small cell lung cancer (NSCLC) patients.

METHODS

This retrospective study included a training cohort (n = 1685) and validation cohort (n = 337) with NSCLC patients treated in First Teaching Hospital of Tianjin University of Traditional Chinese Medicine between January 2018 and January 2021. Cox regression were conducted to identify factors associated with overall survival. The nomogram was built based on 10 significant factors, and evaluated by the concordance index (C-index), calibration curve and receiver operating characteristic (ROC) curve.

RESULTS

In the training cohort, the multivariate cox proportional hazard regression analysis showed that the independent factors for overall survival (OS) included age, brain metastases, hepatic metastases, respiratory system diseases, clinical stages, surgery, absolute count (AC) of CD3⁺, CD4⁺, CD8⁺, and NK cells, which were all applied in the nomogram. The C-index of the nomogram to predict OS was 0.777 (95% CI, 0.751-0.802) in training cohort and 0.822 (95% CI, 0.798-0.846) in validation cohort. The area under the ROC showed a good discriminative ability in both cohorts. Calibration curves presented an excellent consistence between the nomogram predicted probability and actual observation.

CONCLUSIONS

We established a prognostic nomogram to predict OS of the NSCLC patient. This nomogram provided a more quantitative, scientific and objective basis for accurate diagnosis and individual management of NSCLC patients.

Patients with Lower Positive Lymph Nodes Ratio May Benefit from Preoperative Radiotherapy in Stage III Non-Small Cell Lung Cancer

BACKGROUND

Although preoperative radiotherapy (PORT) is a promising therapeutic option for stage III non-small cell lung cancer (NSCLC), the efficacy of this treatment remains controversial. The positive lymph node ratio (PLNR) is recognized as an independent prognostic factor for survival. However, no previous studies have focused on the association between PLNR and PORT in stage III NSCLC.

METHODS

Data were collected from the Surveillance, Epidemiology and End Results (SEER) database, and all patients enrolled in this analysis were diagnosed during 2010-2015. The primary endpoint was overall survival (OS). Univariate and multivariate Cox regression analysis was used to identify factors associated with survival before and after case-control matching. PLNR was defined as the ratio of the number of positive lymph nodes to the total number of retrieved or examined lymph nodes. A cutoff value for PLNR was calculated using an X-tile model.

RESULTS

Overall, 391 patients with PORT and 2814 patients without PORT were enrolled in this study. The cohort after 1:1 case-control matching included 322 patients who received PORT and 322 patients without PORT. PORT was not associated with a significant effect on OS (HR  =  1.14; 95% CI: 0.91-1.43; P  =  0.825). Multivariate Cox regression analysis showed that PLNR (P < 0.001) was independently associated with OS in patients with stage III NSCLC. An X-tile model was used to identify a cutoff value for PLNR: the risk of death was significantly lower in patients with PLNR ≤0.41 who received PORT than in those with PLNR >0.41 who received PORT (HR  =  0.59; 95% CI: 0.38-0.91; P  =  0.015).

CONCLUSION

PLNR may be a prognostic factor for survival in patients with stage III NSCLC who undergo PORT. Lower PLNR is a predictor of better OS and thus warrants further study.

Development and validation of a nomogram for decannulation in patients with neurological injury: A prognostic accuracy study

BACKGROUND

Tracheostomy is a lifesaving procedure provided for patients with severe neurological injury. However, there is a lack of clarity about whether patients can be decannulated within 6 months in those receiving tracheostomy and what factors can be detected as a predictor for decannulation.

OBJECTIVE

The objective of this study was to explore predictive factors of decannulation in patients with neurological injury receiving tracheostomy within 6 months and construct a novel nomogram model for clinical diagnosis and treatment.

METHODS

This retrospective observational study enrolled patients with neurological injury who were admitted to the ICU of neurosurgical department in the First Affiliated Hospital of Nanjing Medical University between January 2016 and March 2021. Patients were divided into decannulation group and cannulation group according to whether tracheostomy tube removal was performed within 6 months after tracheostomy. Multivariable logistic regression analysis was performed to determine associated risk factors with a bootstrap backward selection process. The nomogram to assess the probability of decannulation at 6 months was constructed based on the regression coefficients of the associated factors and validated by bootstrap resampling. Model performance was measured by examining discrimination (Harrell's C-index), calibration (calibration plots), and utility (Kaplan-Meier curves stratified by the tertile of the predicted probability calculated and subgroup analysis stratified by age and intervention).

RESULTS

A total of 40.1% (147/367) of patients decannulated within 6 months. Significant variables in multivariable logistic regression analysis were age (odds ratio [OR], 0.972; 95% confidence interval [CI], 0.954-0.990), National Institutes of Health Stroke Scale (NIHSS) score (OR, 0.936; 95% CI, 0.911-0.963), early rehabilitation (OR, 5.062; 95% CI, 2.889-8.868), shock (OR, 0.175; 95% CI, 0.058-0.533), and secondary surgery (OR, 0.210; 95% CI, 0.078-0.566). The area under receiver operating characteristic curve estimated with these variables was of 0.793 (95% CI, 0.747-0.838; P < 0.001). A nomogram prediction model was constructed to predict the probability of decannulation in tracheostomized patients with a concordance index of 0.788 after internal validation.

CONCLUSION

We developed a nomogram that can predict the probability of decannulation within 6 months in tracheostomized neurological injury patients. The nomogram, including age, NIHSS scores, early rehabilitation, shock, and secondary surgery, may assist clinicians in estimating patients' prognosis.

Analysis of prognostic factors of undifferentiated pleomorphic sarcoma and construction and validation of a prediction nomogram based on SEER database

Background

Undifferentiated pleomorphic sarcoma (UPS) is considered one of the most common types of soft tissue sarcoma (STS). Current studies have shown that the prognosis of UPS is related to some of its clinical characteristics, but no survival prediction model for the overall survival (OS) of UPS patients has been reported. The purpose of this study is to construct and validate a nomogram for predicting OS in UPS patients at 3, 5 years after the diagnosis.

Methods

According to the inclusion and exclusion criteria, 1079 patients with UPS were screened from the SEER database and randomly divided into the training cohort (n = 755) and the validation cohort (n = 324). Patient demographic and clinicopathological characteristics were first described, and the correlation between the two groups was compared, using the Kaplan–Meier method and Cox regression analysis to determine independent prognostic factors. Based on the identified independent prognostic factors, a nomogram for OS in UPS patients was established using R language. The nomogram’s performance was then validated using multiple indicators, including the area under the receiver operating characteristic curve (AUC), consistency index (C-index), calibration curve, and decision curve analysis (DCA).

Results

Both the C-index of the OS nomogram in the training cohort and the validation cohort were greater than 0 .75, and both the values of AUC were greater than 0.78. These four values were higher than their corresponding values in the TNM staging system, respectively. The calibration curves of the Nomogram prediction model and the TNM staging system were well fitted with the 45° line. Decision curve analysis showed that both the nomogram model and the TNM staging system had clinical net benefits over a wide range of threshold probabilities, and the nomogram had higher clinical net benefits than the TNM staging system as a whole.

Conclusion

With good discrimination, accuracy, and clinical practicability, the nomogram can individualize the prediction of 3-year and 5-year OS in patients with UPS, which can provide a reference for clinicians and patients to make better clinical decisions.

An Interpretable Two-Phase Modeling Approach for Lung Cancer Survivability Prediction

Although lung cancer survival status and survival length predictions have primarily been studied individually, a scheme that leverages both fields in an interpretable way for physicians remains elusive. We propose a two-phase data analytic framework that is capable of classifying survival status for 0.5-, 1-, 1.5-, 2-, 2.5-, and 3-year time-points (phase I) and predicting the number of survival months within 3 years (phase II) using recent Surveillance, Epidemiology, and End Results data from 2010 to 2017. In this study, we employ three analytical models (general linear model, extreme gradient boosting, and artificial neural networks), five data balancing techniques (synthetic minority oversampling technique (SMOTE), relocating safe level SMOTE, borderline SMOTE, adaptive synthetic sampling, and majority weighted minority oversampling technique), two feature selection methods (least absolute shrinkage and selection operator (LASSO) and random forest), and the one-hot encoding approach. By implementing a comprehensive data preparation phase, we demonstrate that a computationally efficient and interpretable method such as GLM performs comparably to more complex models. Moreover, we quantify the effects of individual features in phase I and II by exploiting GLM coefficients. To the best of our knowledge, this study is the first to (a) implement a comprehensive data processing approach to develop performant, computationally efficient, and interpretable methods in comparison to black-box models, (b) visualize top factors impacting survival odds by utilizing the change in odds ratio, and (c) comprehensively explore short-term lung cancer survival using a two-phase approach.

Nomogram Based on Inflammatory Biomarkers to Predict the Recurrence of Hepatocellular Carcinoma-A Multicentre Experience

PURPOSE

Our study aimed to identify inflammatory biomarkers and develop a prediction model to stratify high-risk patients for hepatitis B virus-associated hepatocellular carcinoma (HBV-HCC) recurrence after curative resection.

PATIENTS AND METHODS

A total of 583 eligible HBV-HCC patients with curative hepatectomy from Guangdong Provincial People's Hospital (GDPH) and Sun Ya-sen University Cancer Centre (SYSUCC) were enrolled in our study. Cox proportional hazards regression was utilized to evaluate potential risk factors for disease-free survival (RFS). The area under the receiver operating characteristic (ROC) curve (AUC) was utilized to assess the discrimination performance. Calibration plots and decision curve analyses (DCA) were used to evaluate the calibration of the nomogram and the net benefit, respectively.

RESULTS

Based on the systemic inflammation response index (SIRI), aspartate aminotransferase to neutrophil ratio index (ANRI), China Liver Cancer (CNLC) stage and microvascular invasion, a satisfactory nomogram was developed. The AUC of our nomogram for predicting 1-, 2-, and 3-year RFS was 0.767, 0.726, and 0.708 in the training cohort and 0.761, 0.716, and 0.715 in the validation cohort, respectively. Furthermore, our model demonstrated excellent stratification as well as clinical applicability.

CONCLUSION

The novel nomogram showed a higher prognostic power for the RFS of HCC patients with curative hepatectomy than the CNLC, AJCC 8th edition and BCLC staging systems and may help oncologists identify high-risk HCC patients.

Prognostic nomograms for lung neuroendocrine carcinomas based on lymph node ratio: a SEER database analysis

Objective

The current study aimed to explore the prognostic value of the lymph node ratio (LNR) in patients with lung neuroendocrine carcinomas (LNECs).

Methods

Data for 1564 elderly patients with LNECs between 1998 and 2016 were obtained from the Surveillance, Epidemiology, and End Results database. The cases were assigned randomly to training (n = 1086) and internal validation (n = 478) sets. The association between LNR and survival was investigated by Cox regression.

Results

Multivariate analyses identified age, tumor grade, summary stage, M stage, surgery, and LNR as independent prognostic factors for both overall survival (OS) and lung cancer-specific survival (LCSS). Tumor size was also a prognostic determinant for LCSS. Prognostic nomograms combining LNR with other informative variables showed good discrimination and calibration abilities in both the training and validation sets. In addition, the C-index of the nomograms was statistically superior to the American Joint Committee on Cancer (AJCC) staging system in both the training and validation cohorts.

Conclusions

These nomograms, based on LNR, showed superior prognostic predictive accuracy compared with the AJCC staging system for predicting OS and LCSS in patients with LNECs.

Log odds of positive lymph nodes is a robust predictor of survival and benefits from postoperative radiotherapy in stage IIIA‐N2 resected non‐small cell lung cancer

Background

The significance of postoperative adjuvant radiotherapy (PORT) on the survival of resected IIIA‐N2 non–small cell lung cancer (NSCLC) remains controversial. Here, we aimed to determine the predictive value of the three nodal classifications which might aid in PORT decision‐making.

Methods

A total of 4797 patients with stage IIIA‐N2 resected NSCLC were identified in the Surveillance, Epidemiology and End Results (SEER) database and were grouped by whether PORT was administered. Survival analysis was used to identify the patient groups who can benefit from PORT. Multivariate analysis was performed to confirm the independent risk factors for lung cancer‐specific survival (LCSS) and overall survival (OS). A validation cohort of 1184 patients from three medical centers in China were also included.

Results

PORT was not associated with better LCSS and OS in the entire cohort after propensity score matching (PSM). However, in the subgroups of positive lymph nodes 4 (PLN4), lymph node ratio 4 (LNR4), and log odds of positive lymph nodes 4 (LODDS4), PORT exhibited its role in improving LCSS (p < 0.05). Although the three nodal classifications were all identified as independent predictors of LCSS and OS, LODDS classification had the best discriminatory ability and prognostic accuracy for stage IIIA‐N2 patients. Similar results were also obtained in the validation cohort.

Conclusions

The LODDS classification not only exhibited the best prognostic performance in predicting LCSS and OS in stage IIIA‐N2 disease, but also could help tailor individualized PORT.

Prognostic Nomogram Based on the Metastatic Lymph Node Ratio for T1-4N0-1M0 Pancreatic Neuroendocrine Tumors After Surgery

Purpose

This study aimed to investigate the prognostic significance of the metastatic lymph node ratio (LNR) in patients with pancreatic neuroendocrine tumors (pNETs) and to develop and validate nomograms to predict 5-, 7-, and 10-year overall survival (OS) and cancer-specific survival (CSS) rates for pNETs after surgical resection.

Methods

The demographics and clinicopathological information of T_1-4N_0-1M₀ pNET patients between 2004 and 2018 were extracted from the Surveillance, Epidemiology and End Results database. X-tile software was used to determine the best cutoff value for the LNR. Patients were randomly divided into the training and the validation groups. A Cox regression model was used in the training group to obtain independent prognostic factors to develop nomograms for predicting OS and CSS. The concordance index (C-index), calibration curves, area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA) were used to assess the nomograms. Patients were divided into four groups according to the model scores, and their survival curves were generated by the Kaplan–Meier method.

Results

A total of 806 patients were included in this study. The best cutoff value for the LNR was 0.16. The LNR was negatively correlated with both OS and CSS. Age, sex, marital status, primary site, grade, the LNR and radiotherapy were used to construct OS and CSS nomograms. In the training group, the C-index was 0.771 for OS and 0.778 for CSS. In the validation group, the C-index was 0.737 for OS and 0.727 for CSS. The calibration curves and AUC also indicated their good predictability. DCA demonstrated that the nomograms displayed better performance than the American Joint Committee on Cancer (AJCC) TNM staging system (8th edition). Risk stratification indicated that patients with higher risk had a worse prognosis.

Conclusions

The LNR is an independent negative prognostic factor for pNETs. The nomograms we built can accurately predict long-term survival for pNETs after surgery.

Development and Validation of a Nomogram for Predicting Overall Survival in Patients with Second Primary Small Cell Lung Cancer After Non-Small Cell Lung Cancer: A SEER-Based Study

Background

Non-small cell lung cancer (NSCLC) survivors are at an increased risk of developing second primary malignancies, such as small cell lung cancer. This paper sought to establish a prognostic nomogram to assess overall survival (OS) in patients with second primary small cell lung cancer (SPSCLC) after NSCLC.

Methods

420 patients who developed SPSCLC after NSCLC were randomly split into the training and validation groups. A nomogram was established by stepwise regression. Area under the curve (AUC) and calibration plots were applied to assess the prognostic performance of the nomogram. Concordance index (C-index), integrated discrimination improvement (IDI), net reclassification index (NRI) and decision curve analysis (DCA) were performed to compare the nomogram with the American Joint Committee on Cancer (AJCC) 8th staging system. Survival risk classification was constructed based on the nomogram.

Results

Five variables were chosen to construct the nomogram. The AUC showed that it had a satisfactory discrimination ability. All calibration plots displayed good concordance between nomogram and observation. The C-index, IDI, NRI and DCA showed the nomogram was superior to the AJCC 8th staging system. The Kaplan-Meier curves suggested huge differences in prognosis among the three risk groups.

Conclusion

This study build a nomogram and risk stratification system for predicting probabilities of OS in patients with SPSCLC after NSCLC, which can help clinicians in individualized survival assessment and treatment decisions.

The Clinical Outcomes, Prognostic Factors and Nomogram Models for Primary Lung Cancer Patients Treated With Stereotactic Body Radiation Therapy

PURPOSE

Stereotactic body radiation therapy (SBRT) is a standard treatment for early primary lung cancer patients. However, there are few simple models for predicting the clinical outcomes of these patients. Our study analyzed the clinical outcomes, identified the prognostic factors, and developed prediction nomogram models for these patients.

MATERIALS AND METHODS

We retrospectively analyzed 114 patients with primary lung cancer treated with SBRT from 2012 to 2020 at our institutions and assessed patient's clinical outcomes and levels of toxicity. Kaplan-Meier analysis with a log-rank test was used to generate the survival curve. The cut-off values of continuous factors were calculated with the X-tile tool. Potential independent prognostic factors for clinical outcomes were explored using cox regression analysis. Nomograms for clinical outcomes prediction were established with identified factors and assessed by calibration curves.

RESULTS

The median overall survival (OS) was 40.6 months, with 3-year OS, local recurrence free survival (LRFS), distant disease-free survival (DDFS) and progression free survival (PFS) of 56.3%, 61.3%, 72.9% and 35.8%, respectively, with grade 3 or higher toxicity rate of 7%. The cox regression analysis revealed that the clinical stage, immobilization device, and the prescription dose covering 95% of the target area (D95) were independent prognostic factors associated with OS. Moreover, the clinical stage, and immobilization device were independent prognostic factors of LRFS and PFS. The smoking status, hemoglobin (Hb) and immobilization device were significant prognostic factors for DDFS. The nomograms and calibration curves incorporating the above factors indicated good predictive accuracy.

CONCLUSIONS

SBRT is effective and safe for primary lung cancer. The prognostic factors associated with OS, LRFS, DDFS and PFS are proposed, and the nomograms we proposed are suitable for clinical outcomes prediction.

Development and Validation of a Prognostic Model to Predict Overall Survival for Lung Adenocarcinoma: A Population-Based Study From the SEER Database and the Chinese Multicenter Lung Cancer Database

Background: Lung adenocarcinoma (LUAD) is the most common subtype of non-small-cell lung cancer (NSCLC). The aim of our study was to determine prognostic risk factors and establish a novel nomogram for lung adenocarcinoma patients. Methods: This retrospective cohort study is based on the Surveillance, Epidemiology, and End Results (SEER) database and the Chinese multicenter lung cancer database. We selected 22,368 eligible LUAD patients diagnosed between 2010 and 2015 from the SEER database and screened them based on the inclusion and exclusion criteria. Subsequently, the patients were randomly divided into the training cohort (n = 15,657) and the testing cohort (n = 6711), with a ratio of 7:3. Meanwhile, 736 eligible LUAD patients from the Chinese multicenter lung cancer database diagnosed between 2011 and 2021 were considered as the validation cohort. Results: We established a nomogram based on each independent prognostic factor analysis for 1-, 3-, and 5-year overall survival (OS) . For the training cohort, the area under the curves (AUCs) for predicting the 1-, 3-, and 5-year OS were 0.806, 0.856, and 0.886. For the testing cohort, AUCs for predicting the 1-, 3-, and 5-year OS were 0.804, 0.849, and 0.873. For the validation cohort, AUCs for predicting the 1-, 3-, and 5-year OS were 0.86, 0.874, and 0.861. The calibration curves were observed to be closer to the ideal 45° dotted line with regard to 1-, 3-, and 5-year OS in the training cohort, the testing cohort, and the validation cohort. The decision curve analysis (DCA) plots indicated that the established nomogram had greater net benefits in comparison with the Tumor-Node-Metastasis (TNM) staging system for predicting 1-, 3-, and 5-year OS of lung adenocarcinoma patients. The Kaplan-Meier curves indicated that patients' survival in the low-risk group was better than that in the high-risk group (P < .001). Conclusion: The nomogram performed very well with excellent predictive ability in both the US population and the Chinese population.

Lobectomy Versus Sublobectomy in Stage IIIA/N2 Non-Small Cell Lung Cancer: A Population-Based Study

Background

The role lobectomy plays in stage IIIA/N2 non-small cell lung cancer (NSCLC) is controversial for a long time. What’s more, no previous study concentrates on whether sublobectomy can improve survival outcome for these patients, so we performed this population-based study to investigate whether stage IIIA/N2 NSCLC can benefit from these two surgery types and compare survival outcomes after lobectomy and sublobectomy.

Methods

A total of 21,638 patients diagnosed with stage IIIA/N2 NSCLC between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database matched our selection criteria. The study cohort included patients who received no surgery (n = 15,951), sublobectomy (n = 628) and lobectomy (n = 5,059). Kaplan–Meier method, Cox regression analyses, and inverse probability of treatment weighting (IPTW)-adjusted Cox regression were used to illustrate the influence of sublobectomy and lobectomy on overall survival (OS) rates in the study cohort and compare these two surgery types.

Results

Multivariable Cox regression analysis showed sublobectomy [HR: 0.584 (95%CI: 0.531–0.644), P-value <0.001; IPTW-adjusted HR: 0.619 (95%CI: 0.605–0.633), P-value <0.001] and lobectomy [HR: 0.439 (95%CI: 0.420–0.459), P-value <0.001; IPTW-adjusted HR: 0.441 (95%CI: 0.431–0.451), P-value <0.001] were both related to better OS rates compared with no surgery, and lobectomy exhibited better survival than sublobectomy [HR: 0.751 (95%CI: 0.680–0.830), P-value <0.001; IPTW-adjusted HR: 0.713 (95%CI: 0.696–0.731), P-value <0.001]. Moreover, the results in subgroup analyses based on age, tumor size and radiotherapy and chemotherapy strategy in all study cohort were consistent.

Conclusion

Stage IIIA/N2 NSCLC patients could benefit from sublobectomy or lobectomy, and lobectomy provided better OS rates than sublobectomy.

Metastasis Pattern and Survival Analysis in Primary Small Bowel Adenocarcinoma: A SEER-Based Study

Background: Small bowel adenocarcinoma (SBA) is a rare gastrointestinal tumor with high malignancy. The aim of this study was to comprehensively evaluate the distant metastasis pattern and establish nomograms predicting survival for SBA. Methods: From 2010 to 2015, patients diagnosed with SBA were identified based on the Surveillance, Epidemiology, and End Results (SEER) database. Kaplan-Meier survival analysis was applied to compare survival differences between metastasis patterns. Then, univariate and multivariate cox analyses were applied to screened out independent prognostic factors of cancer-specific survival (CSS) and overall survival (OS), and identify the risk factors for metastasis of SBA. To assess the discrimination and calibration of nomograms, the concordance index (C-index), calibration curves, receiver-operating characteristic curve (ROC), and decision curve analysis (DCA) were calculated. Results: Kaplan-Meier curves revealed that metastasis patterns were significantly correlated with CSS (p < 0.001) and OS (p < 0.001). Then, the metastasis pattern was showed to be an independent prognostic factor of OS and CSS in patients with SBA, as well as age, grade, T stage, N stage, surgery, retrieval of regional lymph nodes, and chemotherapy. Combining these factors, we constructed prognostic nomograms, which suggested that the metastasis pattern made the greatest contribution to the survival of patients with SBA. Nomograms for OS and CSS had a C-index of 0.787 and 0.793, respectively. Calibration curves showed an excellent agreement between probability and actual observation in the training and validation cohort. Decision curve analysis also exhibited its clinical value with an improved net benefit. In addition, the models we constructed had better prognostic accuracy and clinical utility than traditional TNM staging based on C-index and ROC. Further, Cox regression analysis showed that old age, poor differentiation, N2, and not receiving chemotherapy were the risk factors for prognosis in patients with metastatic SBA. Conclusion: As an independent prognostic factor, the metastasis pattern exhibited the greatest predictive effect on OS and CSS for patients with SBA. Adjuvant chemotherapy had a positive effect on the survival of patients with SBA. Nomograms for predicting 3-and 5-year OS and CSS of patients with SBA were constructed, which could identify patients with higher risk and might be superior in predicting the survival of patients with SBA than TNM staging.

Applying immune-related lncRNA pairs to construct a prognostic signature and predict the immune landscape of stomach adenocarcinoma

Background: Long noncoding RNAs (lncRNAs) are associated with the survival of cancer patients. We constructed an immune-related lncRNA (irlncRNA) pair signature for stomach adenocarcinoma (STAD).Research design and methods: irlncRNAs were identified via coexpression analysis with immune-related genes. Differentially expressed irlncRNAs (DEirlncRNAs) were paired. Least absolute shrinkage and selection operator (LASSO) and multivariate Cox proportional hazards regression methods were used to construct the signature. We calculated the area under the receiver operating characteristic (ROC) curve and determined the best cutoff value according to the Akaike information criterion (AIC). Patients were divided into high - and low-risk groups, and differences in immune cell infiltration, tumor mutation burden (TMB) and drug treatment effects between the groups were explored according to the risk score.Results: An 8-irlncRNA-pair signature was constructed and proven to be a strong prognosis predictor in STAD patients through external verification. Moreover, the risk score was identified as an independent prognostic factor. There were significant differences in immune cell infiltration and the response to several drug treatments between patients with high and low risk scores, and the risk score was negatively correlated with TMB.Conclusions: The signature consisting of 8 irlncRNA pairs showed good prognostic predictive value.

Prognostic value of baculoviral IAP repeat containing 5 expression as a new biomarker in lung adenocarcinoma: a meta-analysis

BACKGROUND

BIRC5 is associated with the prognosis of a variety of tumors. This meta-analysis aimed to identify whether BIRC5 is associated with the prognosis of lung adenocarcinoma (LUAD).

RESEARCH DESIGN AND METHODS

We conducted an in-depth review of seven Chinese and English databases and two high-throughput sequencing databases according to inclusion and exclusion criteria to find relevant studies. The pooled standardized mean differences (SMDs) and 95% confidence intervals (CIs) for the associations between the BIRC5 expression level and clinicopathological characteristics were calculated, and the pooled hazard ratios (HRs) and 95% CIs were calculated to estimate associations between the BIRC5 expression level and survival outcomes.

RESULTS

In total, 17 studies involving 2887 LUAD patients whose BIRC5 expression level was known were included in this meta-analysis. The BIRC5 expression level was higher in younger patients, males, and smokers and correlated with advanced AJCC, T and N stages but not M stage. A high BIRC5 expression level also correlated with poor overall survival (OS) and progression-free survival (PFS). There was no publication bias in this study.

CONCLUSIONS

This meta-analysis indicates that BIRC5 is a significant biomarker for a poor prognosis and poor clinicopathological outcomes in patients with LUAD.

Competing risk analysis of cardiovascular/cerebrovascular death in T1/2 kidney cancer: a SEER database analysis

Background

Kidney cancer (KC) is associated with cardiovascular regulation disorder and easily leads to cardiovascular and cerebrovascular death (CCD), which is one of the major causes of death in patients with KC, especially those with T1/2 status. However, few studies have treated CCD as an independent outcome for analysis. We aimed to identify and evaluate the key factors associated with CCD in patients with T1/2 KC by competing risk analysis and compared these risk factors with those associated with kidney cancer-specific death (KCD) to offer some information for clinical management.

Methods

A total of 45,117 patients diagnosed with first primary KC in T1/2 status were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. All patients were divided into the CCD group (n = 3087), KCD group (n = 3212), other events group (n = 6312) or alive group (n = 32,506). Patients’ characteristics were estimated for their association with CCD or KCD by a competing risk model. Pearson’s correlation coefficient and variance inflation factor (VIF) were used to detect collinearity between variables. Factors significantly correlated with CCD or KCD were used to create forest plots to compare their differences.

Results

The competing risk analysis showed that age at diagnosis, race, AJCC T/N status, radiation therapy, chemotherapy and scope of lymph node represented different relationships to CCD than to KCD. In detail, age at diagnosis (over 74/1–50: HR = 9.525, 95% CI: 8.049–11.273), race (white/black: HR = 1.475, 95% CI: 1.334–1.632), AJCC T status (T2/T1: HR = 0.847, 95% CI: 0.758–0.946) and chemotherapy (received/unreceived: HR = 0.574, 95% CI: 0.347–0.949) were correlated significantly with CCD; age at diagnosis (over 74/1–50: HR = 3.205, 95% CI: 2.814–3.650), AJCC T/N status (T2/T1: HR = 2.259, 95% CI: 2.081–2.451 and N1/N0:HR = 3.347, 95% CI: 2.698–4.152), radiation therapy (received/unreceived: HR = 2.552, 95% CI: 1.946–3.346), chemotherapy (received/unreceived: HR = 2.896, 95% CI: 2.342–3.581) and scope of lymph nodes (1–3 regional lymph nodes removed/none: HR = 1.378, 95% CI: 1.206–1.575) were correlated significantly with KCD.

Conclusions

We found that age at diagnosis, race, AJCC T status and chemotherapy as the independent risk factors associated with CCD were different from those associated with KCD.

Development and Validation of a Novel Nomogram for Predicting Tumor-Distant-Metastasis in Patients with Early T1-2 Stage Lung Adenocarcinoma

Background

Distant metastasis in early T1-2 (diameter≤5 cm) stage lung adenocarcinoma (ET-LUAD) patients largely affect treatment strategies in clinical practice. However, the associated mechanism remains unclear and related studies is less. This study aimed to establish and validate a novel nomogram to predict the risk of distant metastasis in ET-LUAD.

Methods

A total of 258 patients diagnosed with ET-LUAD and not receiving any treatment were recruited into this study. The patients were randomly divided into a training cohort and validation cohort in a ratio of 1:2. Univariate and multivariate logistic regression analysis was used to select the most significant predictive risk factors associated with distant metastasis in the training cohort. The established nomogram was validated by the consistency index (C-index), calibration curve, and decision curve analysis (DCA).

Results

There were 124 patients with confirmed distant metastasis and 134 patients with non-distant metastases ET-LUAD were enrolled in the study. Multivariate logistic hazards regression analysis identified independent risk factors associated with distant metastasis to include platelet-to-lymphocyte ratios (PLR), lactate dehydrogenase (LDH), neural-specific enolase (NSE), carcinoembryonic antigen (CEA) and cytokeratin 19 fragments (Cyfra211), which were included in the establishment of the nomogram. The nomogram achieved a high consistency (C-index=0.792), good calibration, and high clinical application value in the validation cohort.

Conclusion

The established nomogram can be used to predict distant metastasis in high-risk ET-LUAD nonmetastasis patients and can also be used by doctors to guide preventive and individualized treatment for ET-LUAD patients.

A Prognostic Microenvironment-Related Immune Signature via ESTIMATE (PROMISE Model) Predicts Overall Survival of Patients With Glioma

Objective

In the development of immunotherapies in gliomas, the tumor microenvironment (TME) needs to be investigated. We aimed to construct a prognostic microenvironment-related immune signature via ESTIMATE (PROMISE model) for glioma.

Methods

Stromal score (SS) and immune score (IS) were calculated via ESTIMATE for each glioma sample in the cancer genome atlas (TCGA), and differentially expressed genes (DEGs) were identified between high-score and low-score groups. Prognostic DEGs were selected via univariate Cox regression analysis. Using the lower-grcade glioma (LGG) data set in TCGA, we performed LASSO regression based on the prognostic DEGs and constructed a PROMISE model for glioma. The model was validated with survival analysis and the receiver operating characteristic (ROC) in TCGA glioma data sets (LGG, glioblastoma multiforme [GBM] and LGG+GBM) and Chinese glioma genome atlas (CGGA). A nomogram was developed to predict individual survival chances. Further, we explored the underlying mechanisms using gene set enrichment analysis (GSEA) and Cibersort analysis of tumor-infiltrating immune cells between risk groups as defined by the PROMISE model.

Results

We obtained 220 upregulated DEGs and 42 downregulated DEGs in both high-IS and high-SS groups. The Cox regression highlighted 155 prognostic DEGs, out of which we selected 4 genes (CD86, ANXA1, C5AR1, and CD5) to construct a PROMISE model. The model stratifies glioma patients in TCGA as well as in CGGA with distinct survival outcome (P<0.05, Hazard ratio [HR]>1) and acceptable predictive accuracy (AUCs>0.6). With the nomogram, an individualized survival chance could be predicted intuitively with specific age, tumor grade, Isocitrate dehydrogenase (IDH) status, and the PROMISE risk score. ROC showed significant discrimination with the area under curves (AUCs) of 0.917 and 0.817 in TCGA and CGGA, respectively. GSEA between risk groups in both data sets were significantly enriched in multiple immune-related pathways. The Cibersort analysis highlighted four immune cells, i.e., CD 8 T cells, neutrophils, follicular helper T (Tfh) cells, and Natural killer (NK) cells.

Conclusions

The PROMISE model can further stratify both LGG and GBM patients with distinct survival outcomes.These findings may help further our understanding of TME in gliomas and shed light on immunotherapies.