Univariate Cox Analysis Research Articles

Predicting progression-free survival in sarcoma using MRI-based automatic segmentation models and radiomics nomograms: a preliminary multicenter study.

Some sarcomas are highly malignant, associated with high recurrence despite treatment. This multicenter study aimed to develop and validate a radiomics signature to estimate sarcoma progression-free survival (PFS). The study retrospectively enrolled 202 consecutive patients with pathologically diagnosed sarcoma, who had pre-treatment axial fat-suppressed T2-weighted images (FS-T2WI), and included them in the ROI-Net model for training. Among them, 120 patients were included in the radiomics analysis, all of whom had pre-treatment axial T1-weighted and transverse FS-T2WI images, and were randomly divided into a development group (n = 96) and a validation group (n = 24). In the development cohort, Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression was used to develop the radiomics features for PFS prediction. By combining significant clinical features with radiomics features, a nomogram was constructed using Cox regression. The proposed ROI-Net framework achieved a Dice coefficient of 0.820 (0.791-0.848). The radiomics signature based on 21 features could distinguish high-risk patients with poor PFS. Univariate Cox analysis revealed that peritumoral edema, metastases, and the radiomics score were associated with poor PFS and were included in the construction of the nomogram. The Radiomics-T1WI-Clinical model exhibited the best performance, with AUC values of 0.947, 0.907, and 0.924 at 300days, 600days, and 900days, respectively. The proposed ROI-Net framework demonstrated high consistency between its segmentation results and expert annotations. The radiomics features and the combined nomogram have the potential to aid in predicting PFS for patients with sarcoma.

Nomograms for predicting the prognosis in multiple primary esophageal squamous cell carcinoma

Background Due to its rarity, it is challenging to predict the survival of patients with synchronous multiple primary esophageal squamous carcinomas (SMPESCs). We aimed to construct nomograms to predict survival outcomes and help to make therapeutic strategy for patients with SMPESCs. Materials and Methods The clinical and survival data of 135 patients with SMPESCs were analyzed retrospectively. Univariate and multivariate Cox analyses were used to identify independent prognostic factors. Nomograms were constructed to predict 1-year, 3-year and 5-year disease-free survival (DFS) and overall survival (OS). In addition, we further evaluated the effect of postoperative adjuvant therapy on SMPESCs patients with lymph node metastasis. Results In univariate and multivariate analyses of DFS and OS, age, site of the main lesion, lymph node metastasis, total number of lymph nodes dissected, lactate dehydrogenase level and lymphocyte-to-monocyte ratio were identified as independent prognostic factors. These characteristics were further included to establish nomograms. For the internal validation of the nomogram predictions of survival outcomes, the concordance indices were 0.752 and 0.756, respectively. Decision curve analysis also proved the efficacy of the nomograms. Furthermore, adjuvant therapy had a statistically significant benefit for OS but not DFS in patients with lymph node metastasis. Conclusions These nomograms could effectively predict the 1-year, 3-year and 5-year survival outcomes of patients with SMPESCs. Furthermore, adjuvant therapy has the potential to improve OS in patients with lymph node metastasis.

A real-world study: third-line treatment options for metastatic colorectal cancer

BackgroundNumerous third-line treatment options exist for colorectal cancer. This study aims to assess the efficacy and safety of third-line therapies, including TKIs (fruquintinib, regorafenib) combined with PD-1 inhibitors, and trifluridine/tipiracil combined with bevacizumab, in patients with refractory microsatellite stable metastatic colorectal cancer who have progressed or are intolerant following standard first- and second-line treatments.Materials and methodsThis retrospective analysis collected data from patients with microsatellite stable advanced colorectal adenocarcinoma, diagnosed through histopathology and treated at Henan Provincial Cancer Hospital from May 2019 to April 2023. We compared the efficacy and safety of fruquintinib combined with PD-1 inhibitors, regorafenib combined with PD-1 inhibitors, and trifluridine/tipiracil combined with bevacizumab.ResultsAmong 60 eligible patients with refractory microsatellite stable metastatic colorectal adenocarcinoma, 29 (48.3%) received fruquintinib combined with PD-1 inhibitors, 15 (25%) received regorafenib combined with PD-1 inhibitors, and 16 (26.7%) received trifluridine/tipiracil combined with bevacizumab. The average follow-up period was 12.6 months (ranging from 2.3 to 37.6 months). After third-line treatment, the overall objective response rate (ORR) was 8.6%, and the disease control rate (DCR) was 78.6%. The median overall survival (OS) for the regorafenib, fruquintinib, and trifluridine/tipiracil groups was 19.2 months, 14.0 months, and 16.2 months, respectively, with no statistically significant differences observed. However, there were statistically significant differences in progression-free survival (PFS); the median PFS for the regorafenib group was 6.3 months, for the fruquintinib group was 4.2 months, and for the trifluridine/tipiracil group was 5.4 months. Pairwise comparisons indicated that the PFS for the regorafenib group was similar to that for the trifluridine/tipiracil group, both of which were superior to the fruquintinib group. Cox univariate regression analysis revealed that the presence of liver and peritoneal metastases was associated with PFS in third-line treatment.ConclusionIn the third-line treatment of colorectal cancer, regorafenib combined with PD-1 inhibitors and trifluridine/tipiracil combined with bevacizumab showed superiority over fruquintinib combined with PD-1 inhibitors in terms of PFS, but no statistically significant difference in OS was noted among the three groups.

The clinical features and prognostic implications of the co-mutated TP53 gene in advanced non-small cell lung cancer.

TP53 is a frequently mutated oncogene within non-small cell lung cancer (NSCLC). However, the clinical and prognostic significance of co-mutations in TP53 in patients with advanced NSCLC has not been fully elucidated. A total of 174 patients with advanced NSCLC were enrolled in this study. All patients were subjected to sequencing analysis of tumor-related genes and information such as PD-L1 expression, TMB, and co-mutation changes were collected. Patients were categorized into TP53 mutant and TP53 wild-type groups according to their TP53 mutation status and then statistically analyzed. TP53 mutations were the most common among all patients, accounting for 56.32%, followed by epidermal growth factor receptor mutations at 48.27%. The most common mutation sites in the TP53 mutation group were exons 5-8.TP53 mutations were significantly associated with PD-L1 and TMB levels. Univariate Cox analysis showed that gender and EGFR mutation affected the prognosis of TP53-mutated NSCLC patients, and multivariate Cox regression analysis identified EGFR mutation as an independent risk factor. The OS of NSCLC patients in the TP53 mutation group was significantly shorter than that of the TP53wt group. Survival curves in the TP53/EGFR combined mutation group showed that patients with combined EGFR mutation had a lower survival rate. TP53 mutations are associated with different clinical indicators and have important implications in clinical treatment. TP53 is a poor prognostic factor for NSCLC patients, and TP53/EGFR co-mutation will affect the survival time of patients. TP53/EGFR co-mutation may be a new prognostic marker for NSCLC.

Population data study reveals pain as a possible protective factor against cerebrovascular disease in cancer patients

The purpose of this study is to investigate the relationship between chronic pain and the mortality rate of cerebrovascular disease (CVD) in cancer patients. Thus, we performed a case-control investigation was conducted by utilizing data from the Surveillance, Epidemiology, and End Results (SEER) database between 1975 and 2019. Multiple demographics, pain rating and other clinical characteristics were extracted to assess predictors for the death from CVD in cancer patients. Different machine learning algorithms were applied to construct pain-related prediction model. The analysis involved 16,850 case patients and 710,729 controls. Among cancer patients, approximately 2.3% succumbed to subsequent CVD. Cancer pain (Pain rating II) was associated with a decreased risk of CVD. Univariate and multivariate COX analyses indicated that older age at cancer diagnosis, male gender, single marital status, Black or Other race, and lack of systemic therapy correlated with a higher risk of CVD-related death. Propensity score matching revealed a significantly lower proportion of Pain rating II in the case group. The logistic regression algorithm demonstrated superior predictive ability for 5-year and 10-year CVD risk in cancer patients. Notably, survival time, age, and pain rating emerged as the top three crucial variables. This study firstly investigated pain and various risk factors for CVD in cancer patients, highlighting pain as a novel and possible protective factor for CVD. The development of a risk model based on pain could aid in identifying individuals at high risk for CVD and may inspire innovative strategies for preventing CVD in cancer patients.

Postoperative peritumoral edema is correlated with the prognosis in intracranial meningioma with preoperative peritumoral edema.

Preoperative peritumoral edema (PTE) in intracranial meningiomas is known to be a risk factor for postoperative recurrence. However, there are two groups: those in which preoperative PTE remains and those in which preoperative PTE receded after tumor removal. We aimed to investigate whether postoperative PTE could improve the prediction of prognosis of meningioma with preoperative PTE. We retrospectively reviewed postoperative MRI scans in 3 months after operation of 371 patients with preoperative PTE of meningioma that underwent surgery between 2015 and 2017. All the patients were classified into two different groups according to whether had postoperative PTE receded within 3 months after operation. Clinical manifestations, histopathology characteristics, radiology data and follow-up outcomes were noted. student's t-test and chi-square test for independence were used to compare clinical characteristics. Univariate and multivariate Cox analysis and Kaplan‒Meier methods were utilized to determine the independent effect of postoperative PTE on postoperative recurrence. Multivariate Cox analyses showed that the risk factors of meningioma recurrence: high WHO grades (HR = 4.989, P<0.001), superior sagittal sinus invasion (HR = 2.290, P = 0.047), postoperative PTE in 3 months after operation (HR = 1.804, P = 0.044) and STR (HR = 3.940, P = 0.003). Kaplan-Meier model showed that the progression-free survival of patients with postoperative PTE are shorter than who with postoperative PTE receded in 3 months after operation (HR = 3.30, P = 0.006). According to our research, we found that postoperative PTE in 3 months after operation is related to the outcomes of meningioma with preoperative PTE. Besides, we demonstrated that there were also some factors for recurrence: male, high WHO grades, superior sagittal sinus invasion and STR. These findings highlight the need for prospective study.

Unraveling impact and potential mechanisms of baseline pain on efficacy of immunotherapy in lung cancer patients: a retrospective and bioinformatic analysis

ObjectivePain is a prevalent discomfort symptom associated with cancer, yet the correlations and potential mechanisms between pain and the efficacy of cancer immunotherapy remain uncertain.MethodsNon-small cell lung cancer (NSCLC) patients who received immune checkpoint inhibitors (ICIs) in the inpatient department of Guangdong Provincial Hospital of Chinese Medicine from January 1, 2018, to December 31, 2021, were retrospectively enrolled. Through cox regression analysis, prognostic factors and independent prognostic factors affecting the efficacy of ICIs were identified, and a nomogram model was constructed. Hub cancer-related pain genes (CRPGs) were identified through bioinformatic analysis. Finally, the expression levels of hub CRPGs were detected using an enzyme-linked immunosorbent assay (ELISA).ResultsBefore PSM, a total of 222 patients were enrolled in this study. Univariate and multivariate cox analysis indicated that bone metastasis and NRS scores were independent prognostic factors for the efficacy of ICIs. After PSM, a total of 94 people were enrolled in this study. Univariate cox analysis and multivariate cox analysis indicated that age, platelets, Dnlr, liver metastasis, bone metastasis, and NRS scores were independent prognostic factors for the efficacy of ICIs. A nomogram was constructed based on 6 independent prognostic factors with AUC values of 0.80 for 1-year, 0.73 for 2-year, and 0.80 for 3-year survival. ELISA assay results indicated that the level of CXCL12 significantly decreased compared to baseline after pain was relieved.ConclusionBaseline pain is an independent prognostic factor affecting the efficacy of ICIs in lung cancer, potentially through CXCL12-mediated inflammation promotion and immunosuppression.

A CT-Based Clinical-Radiomics Nomogram for Predicting the Overall Survival to TACE Combined with Camrelizumab and Apatinib in Patients with Advanced Hepatocellular Carcinoma

ObjectivesTo construct a computed tomography (CT)-based clinical-radiomics nomogram for estimating overall survival (OS) in advanced hepatocellular carcinoma (HCC) patients receiving transcatheter arterial chemoembolization (TACE) in combination with camrelizumab and apatinib. MethodsA retrospective recruitment of 150 patients with clinically or pathologically confirmed HCC was conducted, followed by their division into training cohort (n=105) and test cohort (n=45). To generate the radiomics score (Rad-score), a series of analyses were performed, including Pearson correlation analysis, univariate Cox analysis, and least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Subsequently, a clinical-radiomics nomogram was constructed using the Rad-score combined with independent clinical prognostic factors, followed by assessments of its calibration, discrimination, reclassification, and clinical utility. ResultsFive CT radiomics features were selected. The Rad-score showed a significant correlation with OS (P < 0.001). The clinical-radiomics nomogram demonstrated superior performance in estimating OS, with a concordance index (C-index) of 0.840, compared to the radiomics nomogram (C-index: 0.817) and the clinical nomogram (C-index: 0.661). It also exhibited high 1-year and 2-year area under the curves of 0.936 and 0.946, respectively. Additionally, the clinical-radiomics nomogram markedly enhanced classification accuracy for OS outcomes, as evidenced by net reclassification improvement and integrated discrimination improvement. Decision curve analysis confirmed its clinical utility. ConclusionA CT-based clinical-radiomics nomogram exhibits strong potential for predicting OS in advanced HCC patients undergoing TACE combined with camrelizumab and apatinib.

Association between D-dimer-to-albumin ratio and 28-days all-cause mortality in patients with sepsis

We aimed to investigate the correlation between the serum D-dimer (D-D) to albumin (ALB) ratio (DAR) and 28-day all-cause mortality in patients with sepsis. Data from sepsis patients admitted to the intensive care unit (ICU) of Wuhan Fourth Hospital from October 2021 to January 2024 were collected. Univariate cox analysis was performed for mortality factors in sepsis patients, and multiple cox regression models were used to analyze independent mortality risk factors. The receiver operating characteristics (ROC) curve was used to analyze the value of DAR in predicting sepsis mortality, and the Kaplan–Meier method was used to plot the survival curve. A total of 833 patients with sepsis in the ICU of our hospital were selected and divided into alive group (n = 574) and death group (n = 171) according to their 28-day survival. In the death group, D-D and DAR levels were higher, while ALB levels was lower than in the alive group. Spearman analysis found that DAR level were positively correlated with APACHE II and SOFA scores. Multivariate cox regression analysis showed that DAR was an independent predictor of all-cause mortality within 28 days of admission for sepsis patients (HR = 17.956, 95% CI 3.435–93.851, p < 0.001). The ROC curve results showed that the cut-off value of DAR was 0.068, with a sensitivity of 78.4% and a Youden index of 0.375, predicting mortality in sepsis patients, with an area under curve (AUC) of 0.767 (95% CI 0.744–0.790, P < 0.001). Further analysis divided patients into low DAR (DAR < 0.068) and high DAR (DA ≥ 0.068) groups based on the optimal cut-off value. Kaplan–Meier analysis found higher mortality in the high DAR group. DAR is an independent predictor of all-cause mortality within 28 days of admission in sepsis patients. Combining these two indicators can improve clinical treatment guidance and reduce the risk of death.

Prognostic value of the cholesterol-dependent nutritional prognostic index in patients receiving adjuvant chemotherapy after radical esophageal cancer treatment

BackgroundEsophageal cancer is the 6th most common cancer in terms of incidence and the 4th most common cause of mortality in China. Given the limited survival outcomes observed in patients with locally advanced disease managed exclusively with surgical intervention, postoperative treatment is critically important. This study sought to assess the prognostic value of total cholesterol (TC) levels and the prognostic nutritional index (PNI) in patients undergoing postoperative chemotherapy for esophageal cancer.MethodsA total of 101 patients who underwent postoesophagectomy chemotherapy were included in this retrospective analysis. PNI values for prechemotherapy were calculated for each patient [PNI = albumin + 5 × lymphocyte count] and TC. The optimal cutoff values for these indices were calculated from the receiver operating characteristic (ROC) curve. Patients were stratified into three groups on the basis of their PNI and TC levels. A novel nutritional prognostic index, termed the cholesterol-dependent nutritional prognostic index (CPNI), was developed on the basis of the PNI and TC. Univariate and multivariate Cox analyses were employed to determine the associations between each indicator and clinical outcomes.ResultsThe prechemotherapy PNI, TC level, and TNM stage became independent risk factors for OS (p < 0.05). Patients in the high PNI-high TC group had significantly improved DFS and OS compared with those in the low PNI-low TC group (p < 0.001) and had a lower early recurrence rate (P = 0.008). In contrast, patients with a high CPNI had a higher mortality rate.ConclusionThe prechemotherapy PNI combined with TC is an accurate and useful predictor of patient prognosis.

Comparison of multiple machine learning models for predicting prognosis of pancreatic ductal adenocarcinoma based on contrast-enhanced CT radiomics and clinical features.

The aim of this study was to evaluate the prognostic potential of combining clinical features and radiomics with multiple machine learning (ML) algorithms in pancreatic ductal adenocarcinoma (PDAC). A total of 116 patients with PDAC who met the eligibility criteria were randomly assigned to a training or validation cohort. Seven ML algorithms, including Supervised Principal Components, stepwise Cox, Random Survival Forest, CoxBoost, Least absolute shrinkage and selection operation (Lasso), Ridge, and Elastic network, were integrated into 43 algorithm combinations. Forty-three radiomics models were constructed separately using radiomics features extracted from arterial phase (AP), venous phase (VP), and combined arterial and venous phase (AP+VP) images. The concordance index (C-index) of each model was calculated. The model with the highest mean C-index was identified as the best model for calculating the radiomics score (Radscore). Univariate and multivariate Cox analyses were used to identify independent prognostic indicators and create a clinical model for prognosis prediction. The multivariable Cox regression was used to combine Radscore with clinical features to create a combined model. The efficacy of the model was evaluated using the C-index, calibration curves, and decision curve analysis (DCA). The model based on the Lasso+StepCox[both] algorithm constructed using AP+VP radiomics features showed the best predictive ability among the 114 radiomics models. The C-indices of the model in the training and validation cohorts were 0.742 and 0.722, respectively. Based on the results of the univariate and multivariate Cox regression analyses, sex, Tumor-Node-Metastasis (TNM) stage, and systemic inflammation response index were included to build the clinical model. The combined model, incorporating three clinical factors and AP+VP-Radscore, achieved the highest C-indices of 0.764 and 0.746 in the training and validation cohorts, respectively. In terms of preoperative prognosis prediction for PDAC, the calibration curve and DCA showed that the combined model had a good consistency and greatest net benefit. A combined model of clinical features and AP+VP-Radscore screened using multiple ML algorithms has an excellent ability to predict the prognosis of PDAC and may provide a noninvasive and effective method for clinical decision-making.

Effect of dyslipidemia on HBsAg clearance in nucleos(t)ide analogues-experienced chronic hepatitis B patients treated with peginterferon alfa

BackgroundWhile previous reports have shown that hepatitis B virus (HBV) infection affects lipid metabolism and vice versa, the impact of dyslipidemia on the functional cure of HBV infection following peginterferon alfa (PegIFNα) therapy remains unknown. Hence, this study aimed to investigate the effect of dyslipidemia on hepatitis B surface antigen (HBsAg) clearance and develop a nomogram model for predicting patients for whom PegIFNα therapy is indicated.MethodsA total of 160 nucleos(t)ide analogues (NAs)- experienced chronic hepatitis B (CHB) patients treated with PegIFNα (180 µg/week) were enrolled in this study. The relationship between serum lipid and HBsAg clearance was analysed. Univariate and multivariate COX analyses were used to construct and plot the nomogram model. The area under the receiver operating characteristic curve (AUC) and calibration curve were used to evaluate the discrimination and calibration of the model, respectively.ResultsAfter 48 weeks of PegIFNα therapy, a total of 33 patients in the cohort achieved HBsAg clearance. Univariate and multivariate COX analyses indicated that dyslipidemia was significantly associated with HBsAg clearance and was an independent predictor of HBsAg clearance (HR = 0.243, P = 0.001). Kaplan-Meier survival analyses show that cumulative HBsAg clearance was significantly higher in the normolipidemic group than in the dyslipidemia group (log-rank test, P = 0.007). During the treatment, triglyceride showed an increasing trend, while the levels of total cholesterol, high-density lipoprotein, low-density lipoprotein, apolipoprotein A1 and apolipoprotein B decreased. Dyslipidemia and other indicators independently associated with HBsAg clearance were used to construct the nomogram model. The AUC of the model at 36-week and 48-week were 0.879 and 0.856, and the model demonstrated good discrimination and calibration.ConclusionDyslipidemia can affect the antiviral efficacy of PegIFNα in NAs-experienced CHB patients. Our findings suggest that the nomogram model constructed using serum lipid has good predictive power and may help physicians to identify the superior patients for PegIFNα therapy.

Investigation of risk signatures associated with anoikis in thyroid cancer through integrated transcriptome and Mendelian randomization analysis.

Anoikis is intricately associated with the malignant progression of cancer. Thyroid cancer (THCA) is the most common endocrine tumor, metastasis is closely related to treatment response and prognosis of THCA. Hence, it is imperative to comprehensively identify predictive prognostic genes and novel molecular targets for effective THCA therapy. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were utilized to mine differentially expressed anoikis-related (DE-ARGs). Then, the prognostic genes were identified and a risk signature was constructed for THCA using univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) method. Furthermore, the associations between risk signature and immune infiltration, immunotherapy, as well as potential mechanisms of action were determined using multiple R packages and Wilcoxon test. Finally, Mendelian randomized (MR) analysis was conducted to investigate the causal relationship between the prognostic genes and THCA. In total, six prognostic genes (LRRC75A, METTL7B, ADRA1B, TPD52L1, TNFRSF10C, and CXCL8) related to anoikis were identified, and the corresponding risk signature were constructed to assess the survival time of THCA patients. Immunocorrelation analysis demonstrated the anoikis-relevant risk signature could be used to evaluate immunotherapy effects in THCA patients, and the infiltration of immune cells was correlated with the degree of risk in THCA patients. According to two-sample MR analysis, there was the significant causal relationship between CXCL8 and THCA (odds ratio [OR] > 1 & p< 0.05), and the increase of its gene expression would lead to an increased risk of THCA. Furthermore, real-time quantitative polymerase chain reaction (RT-qPCR) confirmed the upregulated expression patterns of these prognostic genes in THCA tissues. In conclusion, we constructed the risk signature related to anoikis for THCA, which might have important clinical significance for improving the quality of life and treatment effect of THCA patients.

Computerized tomography features acting as predictors for invasive therapy in the management of Crohn's disease-related spontaneous intra-abdominal abscess: experience from long-term follow-up.

Decision-making in the management of Crohn's disease (CD)-related spontaneous intra-abdominal abscess (IAA) is challenging. This study aims to reveal predictive factors for percutaneous drainage and/or surgery in the treatment of CD-related spontaneous IAA through long-term follow-up. Data were collected, including clinical manifestations, radiography and treatment strategies, in Chinese patients with CD-related IAA in a tertiary medical center. Univariate and Multivariate Cox analysis were conducted to identify predictors for invasive therapy. Altogether, 48 CD patients were identified as having IAA through enhanced CT scans. The median follow-up time was 45.0 (23.3, 58.0) months. 23 (47.9%) patients underwent conservative medical treatment, and 25 (52.1%) patients underwent percutaneous drainage and/or surgical intervention (invasive treatment group). The 1-, 2-, and 5-year overall survival rates without invasive treatment were 75.0%, 56.1%, and 46.1%, respectively. On univariate Cox analysis, the computerized tomography (CT) features including nonperienteric abscess (HR: 4.22, 95% CI: 1.81-9.86, p = 0.001), max abscess diameter (HR: 1.01, 95% CI: 1.00-1.02, p<0.001) and width of sinus (HR: 1.27, 95% CI: 1.10-1.46, p = 0.001) were significantly associated with invasive treatment. Nonperienteric abscess was significantly associated with invasive treatment on multivariate Cox analysis (HR: 3.11, 95% CI: 1.25-7.71, p = 0.015). A score model was built by width of sinus, location of abscess and max abscess diameter to predict invasive treatment. The AUC of ROC, sensitivity and specificity were 0.892, 80.0% and 90.9% respectively. More than half of CD-related IAA patients needed invasive therapy within 5-year follow-up. The CT features including nonperienteric abscess, larger maximum abscess diameter and width of sinus suggested a more aggressive approach to invasive treatment.

Single-cell sequencing unveils mitophagy-related prognostic model for triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer lacking hormone receptors and HER2 expression, leading to limited treatment options and poor prognosis. Mitophagy, a selective autophagy process targeting damaged mitochondria, plays a complex role in cancer progression, yet its prognostic significance in TNBC is not well understood. This study utilized single-cell RNA sequencing data from the TCGA and GEO databases to identify mitophagy-related genes (MRGs) associated with TNBC. A prognostic model was developed using univariate Cox analysis and LASSO regression. The model was validated across multiple independent cohorts, and correlations between MRG expression, immune infiltration, and drug sensitivity were explored. Nine key MRGs were identified and used to stratify TNBC patients into high-risk and low-risk groups, with the high-risk group showing significantly worse survival outcomes. The model demonstrated strong predictive accuracy across various datasets. Additionally, the study revealed a correlation between higher MRG expression levels and increased immune cell infiltration, as well as potential responsiveness to specific chemotherapeutic agents. The mitophagy-related prognostic model offers a novel method for predicting outcomes in TNBC patients and highlights the role of mitophagy in influencing the tumor microenvironment, with potential applications in personalized treatment strategies.

Efficacy of rechallenge after first-line immunotherapy for advanced gastric cancer: A retrospective real-world study

ABSTRACT We aimed to explore the efficacy of rechallenge after first-line immunotherapy in advanced gastric cancer (AGC) and to analyze the factors affecting prognosis based on clinical characteristics. Eighty-five AGC patients who underwent rechallenged after the failure of first-line treatment with immune checkpoint inhibitors (ICIs) were retrospectively collected from July 2019 to December 2022 in Jiangsu Cancer Hospital. Potential factors affecting prognosis were analyzed by univariate and multivariate Cox analysis. Survival analysis was performed by Kaplan–Meier method and Log rank test. Stratified factors included human epidermal growth factor receptor 2 (HER-2) and programmed cell death-ligand 1 combined positive score (PD-L1 CPS). The objective response rate (ORR) was 15.3%, and the disease control rate (DCR) was 74.1%. The median progression-free survival (PFS) was 4.8 months. Results showed that patients in the I + C group had the best response. The ORR was 20.0% VS 8.7% in the I + C group and I + C + AAD group. The DCR was 78.0% VS 65.2%, and the median PFS was 6.7 VS 4.7 months [hazard ratio (HR): 0.55, 95% confidence interval (CI): 0.30–1.00, p = .022]. The ORR was 20.0% VS 8.3% in the I + C group and I + C + ADC group. The DCR was 78.0% VS 75.0%, and the median PFS was 6.7 VS 4.4 months (HR: 0.59, 95%CI: 0.26–1.30, p = .112). The median PFS was 4.7 VS 4.4 months in the I + C + AAD group and I + C + ADC group (HR: 1.21, 95%CI: 0.60–2.47, p = .580). Adverse events (AEs) were found in 34 patients, mainly including leukopenia 9 (10.6%), and neutropenia 8 (9.4%). The incidence of grade 3–4 AEs was 8.2%. There were no drug-related deaths and all AEs were manageable. Rechallenge after first-line immunotherapy showed good survival benefit and acceptable safety in the therapy of AGC. Especially for patients with HER-2-positive and PD-L1 CPS ≥ 1%, rechallenge may be an effective treatment modality.

Development and validation of a nomogram for predicting overall survival of head and neck adenoid cystic carcinoma

This study aimed to develop and validate a nomogram using clinical variables to guide personalized treatment strategies for adenoid cystic carcinoma of the head and neck (ACCHN). Data from 1069 patients with ACCHN diagnosed between 2004 and 2015 in the Surveillance, Epidemiology, and End Results (SEER) database were used to construct the nomogram. External validation was performed using an independent cohort of 70 patients from Fujian Cancer Hospital. Multivariate Cox regression analysis was conducted using IBM SPSS version 26.0 and R Software version 4.2.3. The concordance index (C-index) and receiver operating characteristic (ROC) curves were used to assess the predictive accuracy of the nomogram. Age, tumor site, surgery, N stage, M stage, and TNM stage were identified as independent prognostic factors through univariate and multivariate Cox analyses. The nomogram demonstrated superior predictive performance compared to the TNM staging system, effectively stratifying patients into high-risk and low-risk groups. This nomogram offers a valuable tool for predicting overall survival in patients with ACCHN and tailoring individualized treatment approaches.

Stereotactic radiosurgery (SRS) for patients with brainstem cerebral cavernous malformations (CCMs): an international, multicentric study

Brainstem cerebral cavernous malformations (CCM) are clinically more aggressive compared to superficial CCMs. Due to their location, resection can be challenging, making stereotactic radiosurgery (SRS) an attractive alternative for symptomatic patient. Brainstem CCM patients (n = 170) were treated with Gamma Knife SRS at 11 radiosurgical centers. Hemorrhagic risk reduction, risk factors of post-SRS hemorrhage, and clinical outcomes were retrospectively analyzed. Most patients had a single (165/170 patients) brainstem CCMs treated; the majority of CCMs (165/181) presented with bleeding. Single-session SRS decreased the risk of repeat hemorrhage in patients with hemorrhagic brainstem CCM (HR: 0.17, p < 0.001) using recurrent multivariate analysis. The annual hemorrhage rate decreased from 14.8 per 100 CCM-years before SRS to 2.3 after treatment. Using univariate Cox-analysis, the probability of a new hemorrhages after SRS was reduced for patient older than 35 years (HR = 0.21, p = 0.002) and increased with a margin dose > 13 Gy (HR = 2.57, p = 0.044). Adverse radiation effect (ARE) occurred in 9 patients (5.3%) and was symptomatic in four (2.4%). At a median follow-up of 3.4 years (Inter-quartile range: 5.4), 13 patients (8.0%) had a worsened clinical status, with the treated CCM being the cause in 5.6% (10) of the patients. Single-session SRS decreased the risk of repeat hemorrhage in patients with hemorrhagic brainstem CCM and conveyed this benefit with a low risk of advrse radiation effects (ARE) and worsening clinical status.

Survival risk stratification based on prognosis nomogram to identify patients with esophageal squamous cell carcinoma who may benefit from postoperative adjuvant therapy

ObjectiveThe purpose of the study is to develop a prognosis nomogram for esophageal squamous cell carcinoma (ESCC) patients with radical resection and to identify patients who may benefit from postoperative adjuvant radiotherapy/chemoradiotherapy through survival risk stratification.MethodsWe retrospectively enrolled patients who underwent esophagectomy in the First Affiliated Hospital of Nanjing Medical University from July 2015 to June 2017. Patients with stage I-III esophageal squamous cell carcinoma who received radical R0 resection with or without postoperative adjuvant radiotherapy/chemoradiotherapy were included. Further, patients were randomly allocated into two groups (training and validation cohorts) with a distribution ratio of 7:3. The prognosis nomogram was constructed based on independent factors determined by univariate and multivariate Cox analyses. The area under the receiver operating characteristic curve (AUC) and calibration curve were adopted to evaluate the discriminative ability and reliability of the nomogram. The accuracy and clinical practicability were respectively assessed by C-index values and decision curve analysis (DCA), and further contrasted the nomogram model and the eighth edition of the American Joint Committee on Cancer (AJCC) TNM staging system. In addition, survival risk stratification was further performed according to the nomogram, and the effect of postoperative adjuvant therapy on each risk group was appraised by the Kaplan-Meier survival analysis.ResultsA total of 399 patients with esophageal squamous cell carcinoma were recruited in this study, including the training cohort (n = 280) and the validation cohort (n = 119). The nomogram-related AUC values ​​for 1, 3, and 5-year OS were 0.900, 0.795, and 0.802, respectively, and 0.800, 0.865, 0.829 in the validation cohort, respectively. The slope of the calibration curve for both cohorts was close to 1, indicating good consistency. The C-index value of the nomogram was 0.769, which was higher than that of the AJCC 8th TNM staging system by 0.061 (p < 0.001). Based on the prognosis nomogram, patients were stratified into three risk groups (low, medium, and high), and there were obvious differences in prognosis among the groups (p < 0.001). Furthermore, postoperative adjuvant therapy has been shown to enhance the 5-year survival rate by over 15% among patients classified as medium- and high-risk.ConclusionThe constructed nomogram as developed resulted in accurate and effective prediction performance in survival outcomes for patients with stage I-III esophageal squamous cell carcinoma who underwent radical R0 resection, which is superior to the AJCC 8th TNM staging system. The survival risk stratification had potential clinical application to guide further personalized adjuvant therapy.

Myocardial parametric mapping in patients with suspected acute myocarditis: a prognosis study

Abstract Background T1 mapping and T2 mapping have become essential components of the 2018 Lake Louise criteria and obtained excellent results in diagnosing myocarditis. However, their prognostic value in acute myocarditis has not yet been well recognized or established. Purpose Our study aims to investigate the prognostic value of T1 mapping, T2 mapping, and extracellular volume fraction (ECV) in a large cohort of patients with suspected acute myocarditis. Materials Patients meeting the recommended clinical criteria for suspected acute myocarditis were consecutively enrolled. The primary endpoint is the composite of cardiac death, heart failure hospitalization, heart transplantation, sustained ventricular arrhythmia, and recurrent myocarditis, defined as major adverse cardiovascular events (MACE). All patients underwent CMR at 3.0 T scanner using a standardized, routine imaging protocol, and the three short-axis view slices (basal, mid-ventricular, and apical) were divided into 16 segments according to the American Heart Association 17-segment model (apex excluded). We also averaged the native T1 values, ECV, and T2 values of all 16 segments to get global T1 and ECV fraction values, respectively. Statistically significant parameters from univariate Cox analyses were put into multivariate Cox analysis. Results A total of 235 patients (150 men; 32±13 years) were enrolled in this study. During a mean follow-up of 43.0±3.6 months, MACE occurred in 37 patients (15.7%) and was univariably associated with heart failure presentation, left ventricular ejection fraction, left ventricular end-systolic volume index, left ventricular end-diastolic volume index, native T1 and ECV. Patients with MACE showed higher global native T1, ECV, and T2 values (1348±59 vs 1266±51, p=&amp;lt;0.001; 40.0±8.7 vs 32.8±5.9, p&amp;lt;0.001; 63.4±12.1 vs. 55.5±9.1, p=0.011), and were more likely to have tissue changes in the interventricular septum and anterior wall (Figure 1). In a series of nesting multivariable Cox regression models, the addition of native T1 (per 10-ms increase: HR, 1.128; 95% CI: 1.043, 1.220; p = 0.003; Harrell’s C-index = 0.833) or ECV (per 5% increase: HR, 1.382; 95% CI: 1.060, 1.802; p = 0.017; Harrell’s C-index = 0.847) improved prognostication compared with the model based on clinical variables, left ventricular ejection fraction, and septal late gadolinium enhancement (Harrell’s C-index = 0.762) (Figure 2). T2 in multivariate Cox regression analysis didn’t show predictive value, but his inclusion increased the C-index of the model to 0.814. Conclusions Myocardial parametric mapping not only holds substantial diagnostic value but also plays a critical role in the prognostic assessment and risk prediction of myocarditis. Their utilization in these contexts enhances the accuracy and effectiveness of clinical evaluations and decision-making processes.