Clinicopathological and Imaging Features Predictive of Clinical Outcome in Metaplastic Breast Cancer

BACKGROUND

Metaplastic breast cancer (MC) is a rare disease, thus it is difficult to study its clinical outcomes.

OBJECTIVES

To investigate whether any clinicopathological or imaging features were associated with clinical outcome in MC.

METHODS

We retrospectively evaluated the clinicopathological and imaging findings, and the clinical outcomes of seventy-two pathologically confirmed MCs. We then compared these parameters between triple-negative (TNMC) and non-TNMCs (NTNMC).

RESULTS

Oval or round shape, and not-circumscribed margin were the most common findings on mammography, ultrasound (US), and magnetic resonance imaging (MRI). It was mostly a mass without calcification on mammography, and revealed complex or hypoechoic echotexture, and posterior acoustic enhancement on US, and rim enhancement, wash-out kinetics, peritumoral edema, and intratumoral necrosis on MRI. Of all 72, 64 were TNMCs, and eight were NTNMCs. Clinicopathological and imaging findings were similar between the two groups, except that MRI showed peritumoral edema more frequently in TNMCs than NTNMCs (p=0.045). There were 21 recurrences and 13 deaths. Multivariable analysis showed that larger tumor size and co-existing DCIS were significantly predictive of Disease free survival (DFS), and larger tumor size and neoadjuvant chemotherapy were significantly predictive of overall survival (OS).

CONCLUSION

MC showed characteristic imaging findings, and some variables associated with survival outcome may help to predict prognosis.

Duration of SARS-CoV-2 RNA detection in COVID-19 patients in home isolation, Rhineland-Palatinate, Germany, 2020 - an interval-censored survival analysis

We analysed consecutive RT-qPCR results of 537 symptomatic coronavirus disease (COVID-19) patients in home quarantine. Respectively 2, 3, and 4 weeks after symptom onset, 50%, 25% and 10% of patients had detectable RNA from severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). In patients with mild COVID-19, RNA detection is likely to outlast currently known periods of infectiousness by far and fixed time periods seem more appropriate in determining the length of home isolation than laboratory-based approaches.

Comprehensive analysis of a long non-coding RNA-associated competing endogenous RNA network in glioma

Long non-coding RNAs (lncRNAs) can act as competing endogenous RNAs (ceRNAs), interacting with microRNAs (miRNAs) and playing an important role in tumor progression. However, the role of lncRNA-mediated ceRNAs in glioma remains largely unknown. The present study aimed to identify novel lncRNAs and their associated function in glioma. RNA sequencing and corresponding clinical data from patients with glioma were obtained from The Cancer Genome Atlas. A total of 598 glioma tissues and 5 normal brain tissues were analyzed in the present study. The differentially expressed (DE) lncRNAs, mRNAs and miRNAs were identified using R packages and were used to construct a ceRNA network. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were performed to investigate the biological functions of the DEmRNAs. Kaplan-Meier curve analysis was performed to investigate the association between DElncRNA expression and patient outcome. A total of 752 DElncRNAs, 2,079 DEmRNAs and 113 DEmiRNAs were identified between glioma and normal tissues. A lncRNA-miRNA-mRNA ceRNA network consisting of 61 lncRNAs, 12 miRNAs and 92 mRNAs was constructed. Survival analysis indicated that 36 DElncRNAs, 72 DEmRNAs and 3 DEmiRNAs were associated with overall survival in patients with glioma. The present study identified novel lncRNAs associated with survival prognosis and may facilitate further investigation of lncRNA-mediated ceRNA regulatory mechanisms in glioma.

Prognosis and Risk Factors of Coronary Artery Lesions before Immunoglobulin Therapy in Children with Kawasaki Disease

Background:

Many children with Kawasaki disease develop coronary artery lesions before intravenous immunoglobulin treatment. However, little data are available on the prognosis of children with Kawasaki disease who developed coronary artery lesions before intravenous immunoglobulin treatment.

Aims:

To explore the outcomes of coronary artery lesions before intravenous immunoglobulin treatment in children with Kawasaki disease and analyze the factors that influence the duration of coronary artery lesions.

Study Design:

Retrospective cohort study.

Methods:

All patients with Kawasaki disease who developed coronary artery lesions before intravenous immunoglobulin treatment in our hospital from January 2009 to December 2014 were reviewed. A Cox proportional hazards model was used to determine the factors influencing the prognosis of coronary artery lesions.

Results:

Among 182 patients included, 28.6% were male, 83.50% were younger than 36 months, and 181 exhibited resolution of coronary artery lesions 2 years after disease onset. The median duration of coronary artery lesions was 31 days, and the proportion of coronary artery lesions was 52% at 1 month, 35% at 2 months, 33% at 3 months, 25% at 6 months, 14% at 1 year, and 0.5% at 2 years. The univariate analysis showed that overweight status, higher platelet count, lower albumin level, and starting treatment more than 10 days after disease onset were factors that possibly affect the duration of coronary artery lesions in children. The multivariate Cox regression analysis showed that female sex (adjusted hazard ratio, 1.661; 95% confidence interval, 1.117-2.470) was an independent protective factor, and overweight status (adjusted hazard ratio, 0.469; 95% confidence interval, 0.298-0.737), higher platelet count (adjusted hazard ratio, 0.649; 95% confidence interval, 0.443-0.950), and starting treatment more than 10 days after disease onset (adjusted hazard ratio, 0.392; 95% confidence interval, 0.215-0.716) were independent risk factors for a longer duration of coronary artery lesions.

Conclusion:

The average duration of coronary artery lesions before intravenous immunoglobulin therapy in children with Kawasaki disease is approximately 1 month. Male gender, overweight status, higher platelet count, and initiation of treatment more than 10 days after the onset of the disease are independent risk factors for longer-lasting coronary artery lesions.

Predictors of Time to Sputum Culture Conversion Among Drug-Resistant Tuberculosis Patients in Oromia Region Hospitals, Ethiopia

Purpose

Multi-drug-resistant tuberculosis occurs when the tuberculosis bacteria develop resistance to at least the two most effective first-line anti-tuberculosis drugs, isoniazid and rifampicin. Sputum culture conversion is one of the indicators to monitor patients’ prognosis throughout the treatment. Hence, this study aimed to assess time to culture conversion and its determinants among drug-resistant tuberculosis patients.

Patients and Methods

A total of 228 drug-resistant tuberculosis patients in selected hospitals in Oromia region, Ethiopia, were included in this study. Descriptive statistics like median time to sputum smear and culture conversion were computed. Bivariate and multivariate Cox proportional hazard models were used to identify the independent predictors of time to culture conversion. The adjusted hazard ratio (AHR) with 95% confidence interval (CI) was used to report the strength of association. Statistical significance was declared at p <0.05.

Results

The median age of the study participants was 28 years with inter-quartile range of (IQR) of 22–32 years, and 60% of the patients were male. The median time to culture conversion was 61 days (IQR: 34–92 days). The proportion of sputum culture conversion at 2nd, 4th, and 6th months of treatment initiation was 47%, 82.5%, and 89%, respectively. The final adjusted multivariate Cox proportional hazard model revealed that patients with massive effusion on chest radiographic finding had a 60%-decreased culture conversion time (AHR: 0.4, 95% CI: 0.1–0.9). Patients with abnormalities without cavitations (AHR: 0.5, 95% CI: 0.2–0.9) and those with uninterpreted findings (AHR: 0.3 95% CI: 0.1–0.5) had delayed culture conversion time.

Conclusion

Chest radiographic findings such as massive effusion, abnormalities without cavitations, and uninterpreted findings were found to be predictors of time to sputum culture conversion. Patients with such characteristics have prolonged culture conversion time. Hence, they may need special attention during the treatment.

Prognostic Significance of Rab27A and Rab27B Expression in Esophageal Squamous Cell Cancer

Purpose

Rab27A and Rab27B, members of the Rab family of small GTPases, have aberrant expression and exert different roles in various cancers. However, their expression and potential prognostic values in esophageal squamous cell cancer (ESCC) still remain elusive. In the present study, we explored the association of Rab27A and Rab27B expression with clinical significance and prognosis in ESCC.

Patients and Methods

A total of 100 surgically resected ESCC tissues were examined to evaluate Rab27A and Rab27B expression levels using the immunohistochemistry method. The relationship of Rab27A and Rab27B with clinicopathological features and prognosis was analyzed. We also investigated the correlation between Rab27A and Rab27B through external and internal validation.

Results

High-expression Rab27A was found to be significantly correlated with N (p=0.045) and TNM (p=0.005) stage, while up-regulated Rab27B was remarkably associated with N stage (p=0.033), TNM stage (p=0.009), and differentiation (p=0.013). High expression of both Rab27A and Rab27B had a worse overall survival (OS) rate. In addition, multivariate Cox regression analyses were utilized to validate that Rab27B expression is an independent prognostic factor for unfavorable OS. Further combined analyses showed that the Rab27A^low/B^low group had a superior OS rate than the Rab27A^high/B^low group, Rab27A^low/B^high group, and Rab27A^high/B^high group. Nevertheless, the latter three groups displayed rare significance between each two comparisons. Furthermore, our data demonstrated that Rab27A expression was positively correlated with Rab27B expression, which were also verified in TCGA datasets.

Conclusion

Rab27A and Rab27B expression levels could be potentially novel prognostic biomarkers in ESCC.

TRPV1 acts as a Tumor Suppressor and is associated with Immune Cell Infiltration in Clear Cell Renal Cell Carcinoma: evidence from integrated analysis

Differential expression of TRPV1 has been detected in many cancer types, including clear cell renal cell carcinoma (ccRCC). However, the clinical significance of TRPV1 expression profile in ccRCC has not been comprehensively elucidated. In this study, TRPV1 expression in ccRCC and other cancer types was analyzed based on data from the GEO and Oncomine databases. Immunohistochemical (IHC) staining was performed for further validation in human ccRCC tissue chips. Survival and correlation analyses of TRPV1 were conducted using Kaplan-Meier Plotter (KM-Plotter) and the Tumor IMmune Estimation Resource (TIMER) database. TRPV1 exhibited a low expression profile in 2 GEO datasets (GSE6344, GSE36895) and 4 Oncomine datasets (Gumz, Lenburg, Beroukhim 1 and Beroukhim 2), as also confirmed by IHC staining. Survival analysis indicated that high enrichment of TRPV1 significantly predicted a better overall survival (OS) and disease-free survival (DFS) of 1, 3, 5 and 10 years in ccRCC patients. TIMER analysis showed that TRPV1 copy number alterations (CNA) were closely related to immune cell infiltration. The detailed results indicated that TRPV1 expression was positively correlated with the infiltration level of CD4+ T cells, but negatively correlated with B cells, macrophages, and dendritic cells infiltration. In addition, TRPV1 might also be inversely related to abundance of the regulatory T cells (Treg) and the M2 subset of macrophages. Finally, we found that TRPV1 expression was tightly associated with several key molecules of the classical pathways in ccRCC, such as VHL, TP53, HIF1A, MTOR, MAPK1, MET, CTNNB1, etc. Our research work suggests that TRPV1 is a novel tumor suppressor and prognosis marker for ccRCC and is of great value for further exploration.

Analysis of intensity-modulated radiotherapy for patients with nasopharyngeal carcinoma

The present study aimed to retrospectively analyze the survival outcomes and prognostic factors for patients with nasopharyngeal carcinoma (NPC) receiving intensity-modulated radiotherapy (IMRT).Clinical data was collected from 691 patients with NPC receiving IMRT from January 2009 to August 2015. A survival analysis was performed and prognostic factors were analyzed using the Kaplan-Meier method, the Cox proportional hazards regression model, and the log-rank test.The median follow-up time was 62.8 months. Sixty-three patients experienced relapse, 44 cases (70%) of which occurred within 3 years. Six cases (9.5%) remained in remission for over 5 years. Seventy-two patients developed metastasis, 63 cases (87.5%) of which occurred within 3 years and only 1 case occurred after 5 years (1.3%). Five-year disease special survival (DSS), progression free survival, locoregional recurrence free survival, and distant metastasis free survival were 86.5%, 82.5%, 90.7%, and 89.4%, respectively in patients with NPC. Patients with stage III NPC with and without induction chemotherapy had 5-year DSS rates of 95.8% and 89.3%, respectively (P = .00). Patients with stage IVa NPC with and without induction chemotherapy had 5-year DSS rates of 73.1% and 68.9%, respectively (P = .04). The 5-year DSS rates of patients with stage III with or without concurrent chemotherapy were 92.8% and 85.5%, respectively (P = .04). The 5-year DSS rates of patients with stage IV with or without concurrent chemotherapy were 72.7% and 53.0% (P = .02).IMRT improves the survival rate of patients with NPC. Recurrence and metastasis mainly occur within 2 to 3 years after radiotherapy. Induction and concurrent chemotherapy improve the 5-year DSS of patients with locally advanced NPC.

Analysis of noisy survival data with graphical proportional hazards measurement error models

In survival data analysis, the Cox proportional hazards (PH) model is perhaps the most widely used model to feature the dependence of survival times on covariates. While many inference methods have been developed under such a model or its variants, those models are not adequate for handling data with complex structured covariates. High-dimensional survival data often entail several features: (1) many covariates are inactive in explaining the survival information, (2) active covariates are associated in a network structure, and (3) some covariates are error-contaminated. To hand such kinds of survival data, we propose graphical PH measurement error models and develop inferential procedures for the parameters of interest. Our proposed models significantly enlarge the scope of the usual Cox PH model and have great flexibility in characterizing survival data. Theoretical results are established to justify the proposed methods. Numerical studies are conducted to assess the performance of the proposed methods.

Identification of differentially expressed metastatic genes and their signatures to predict the overall survival of uveal melanoma patients by bioinformatics analysis

AIM

To identify metastatic genes and miRNAs and to investigate the metastatic mechanism of uveal melanoma (UVM).

METHODS

GSE27831, GSE39717, and GSE73652 gene expression profiles were downloaded from the Gene Expression Omnibus (GEO) database, and the limma R package was used to identify differentially expressed genes (DEGs). Gene Ontology (GO) term enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed using the DAVID online tool. A comprehensive list of interacting DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes (STRING) database and Cytoscape software. The Cytoscape MCODE plug-in was used to identify clustered sub-networks and modules of hub genes from the protein-protein interaction network. GEPIA online software was used for survival analysis of UVM patients (n=80) from the The Cancer Genome Atlas (TCGA) cohort. OncomiR online software was used to find that the miRNAs were associated with UVM prognosis from the TCGA cohort. TargetScan Human 7.2 software was then used to identify the miRNAs targeting the genes.

RESULTS

There were 1600 up-regulated genes and 1399 down-regulated genes. The up-regulated genes were mainly involved in protein translation in the cytosol, whereas the down-regulated genes were correlated with extracellular matrix organization and cell adhesion in the extracellular space. Among the 2999 DEGs, five genes, Znf391, Mrps11, Htra3, Sulf2, and Smarcd3 were potential predictors of UVM prognosis. Otherwise, three miRNAs, hsa-miR-509-3-5p, hsa-miR-513a-5p, and hsa-miR-1269a were associated with UVM prognosis.

CONCLUSION

After analyzing the metastasis-related enriched terms and signaling pathways, the up-regulated DEGs are mainly involved in protein synthesis and cell proliferation by ribosome and mitogen-activated protein kinase (MAPK) pathways. However, the down-regulated DEGs are mainly involved in processes that reduced cell-cell adhesion and promoted cell migration in the extracellular matrix through PI3K-Akt signaling pathway, focal adhesion, and extracellular matrix-receptor interactions. Bioinformatics and interaction analysis may provide new insights on the events leading up to the development and progression of UVM.

Predictors of Time to Discontinuation of Levodopa-Carbidopa Intestinal Gel Infusion: A Retrospective Cohort Study

Background:

Continuous intra-duodenal infusion of levodopa-carbidopa intestinal gel (LCIG) is a well-established therapy for patients with advanced Parkinson’s disease (PD) suffering from motor complications despite optimized treatment with oral dopaminomimetics. However, time to discontinuation of treatment with LCIG varies considerably between patients, ranging from a few months to more than ten years. To improve the selection of candidates for LCIG, knowledge of prognostic factors is of paramount importance.

Objective:

To explore baseline predictors of time to discontinuation of LCIG.

Methods:

In this two-center retrospective cohort study, we reviewed the medical files of 98 PD patients treated with LCIG between April 2006 and December 2015 (53% male; mean age: 66.2 years; mean disease duration: 12.3 years). Baseline patient characteristics were used as covariates in Cox regression models.

Results:

During follow-up (mean observation time: 2.6 years; range: 0.1–9.3) eighteen patients discontinued treatment (18.4%), while seven patients died (7.1%). Median duration of treatment with LCIG, estimated with Kaplan-Meier analysis, was 7.8 years (95% CI: 6.7–9.0). Disease duration (in years) at baseline was a statistically significant predictor of time to discontinuation of LCIG (HR: 0.85; 95% CI: 0.75–0.96, p = 0.006). All other characteristics studied, e.g. age >70 years, did not show statistically significant associations with the total duration of treatment with LCIG.

Conclusion:

Our findings show a low overall rate of discontinuation of LCIG infusion, with a median duration of treatment of 7.8 years. Shorter disease duration at baseline appeared to be a predictor of earlier discontinuation of LCIG.

Profiling of Mitochondrial DNA Heteroplasmy in a Prospective Oral Squamous Cell Carcinoma Study

While a shift in energy metabolism is essential to cancers, the knowledge about the involvement of the mitochondrial genome in tumorigenesis and progression in oral squamous cell carcinoma (OSCC) is still very limited. In this study, we evaluated 37 OSCC tumors and the corresponding benign mucosa tissue pairs by deep sequencing of the complete mitochondrial DNA (mtDNA). After extensive quality control, we identified 287 variants, 137 in tumor and 150 in benign samples exceeding the 1% threshold. Variant heteroplasmy levels were significantly increased in cancer compared to benign tissues (p = 0.0002). Furthermore, pairwise high heteroplasmy frequency difference variants (∆HF% > 20) with potential functional impact were increased in the cancer tissues (p = 0.024). Fourteen mutations were identified in the protein-coding region, out of which thirteen were detected in cancer and only one in benign tissue. After eight years of follow-up, the risk of mortality was higher for patients who harbored at least one ∆HF% > 20 variant in mtDNA protein-coding regions relative to those with no mutations (HR = 4.6, (95%CI = 1.3-17); p = 0.019 in primary tumor carriers). Haplogroup affiliation showed an impact on survival time, which however needs confirmation in a larger study. In conclusion, we observed a significantly higher accumulation of somatic mutations in the cancer tissues associated with a worse prognosis.

Investigation of the association between C-X-C motif chemokine receptor subunits and tumor infiltration levels and prognosis in patients with early-stage pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the malignancies with the highest morality rate due to postoperative local invasion and distant metastasis. Although C-X-C motif chemokine receptor (CXCR) subunits have been reported as prognostic indicators in gastric cancer, the prognostic value of CXCR subunits in PDAC remains poorly understood. In the present study, the expression levels and biological functions of CXCR subunits were investigated using multiple publicly accessible bioinformatic platforms and databases. Survival analysis was used to evaluate the prognostic value of CXCR subunits in 112 early-stage PDAC cases by setting the median expression levels as the cut-off values. A nomogram was constructed to combine CXCR subunit expression levels and clinical data for prognosis prediction. Moreover, the association between CXCR subunit expression levels and tumor infiltration levels were detected in PDAC. The expression levels of CXCR subunits were elevated in PDAC tumor tissues. In the multivariate Cox proportional risk regression model, high CXCR2, CXCR4 and CXCR6 expression levels in early-stage PDAC were associated with a more favorable prognosis. Further, it was demonstrated that the differential expression levels of CXCR subunits in PDAC for combined survival analysis could contribute to risk stratification. The nomogram model demonstrated the contribution of CXCR subunits and clinical features in the prognosis of PDAC. Gene Set Enrichment Analysis suggested that CXCR subunits serve a role in immunomodulatory functions. The expression levels and somatic copy number alterations of CXCR subunits were associated with tumor infiltration levels in PDAC. CXCR subunits were associated with prognosis in patients with early-stage PDAC and may be potential drug targets for the treatment of pancreatic cancer.

Obesity and risk of infections: results from men and women in the Swedish National March Cohort

BACKGROUND

Previous studies have shown an association between body mass index (BMI) and infections, but the literature on type-specific community acquired infections is still limited.

METHODS

We included 39 163 Swedish adults who completed a questionnaire in September 1997 and were followed through record-linkages until December 2016. Information on BMI was self-reported and infections were identified from the Swedish National Patient Register using International Classification of Diseases (ICD), Tenth Revision (ICD-10) codes. We fitted multivariable Cox proportional hazards models for time-to-first-event analysis, and we used extensions of the standard Cox model when repeated events were included.

RESULTS

During a 19-year follow-up 32% of the subjects had at least one infection requiring health care contact, leading to a total of 27 675 events. We found an increased incidence of any infection in obese women [hazard ratio (HR) = 1.22; 95% confidence interval (CI) = 1.12; 1.33] and obese men (HR = 1.25; 95% CI = 1.09; 1.43) compared with normal weight subjects. For specific infections, higher incidences were observed for skin infections in both genders (HR = 1.76; 95% CI = 1.47; 2.12 for obese females and HR = 1.74; 95% CI = 1.33; 2.28 for obese males) and gastrointestinal tract infections (HR = 1.44; 95% CI = 1.19; 1.75), urinary tract infections (HR = 1.30; 95% CI = 1.08; 1.55) and sepsis (HR = 2.09; 95% CI = 1.46; 2.99) in obese females. When accounting for repeated events, estimates similar to the aforementioned ones were found.

CONCLUSIONS

Obesity was associated with an increased risk of infections in both genders. Results from multiple-failure survival analysis were consistent with those from classic Cox models.

Development of an immune-related prognostic model for pediatric acute lymphoblastic leukemia patients

Background

Acute lymphoblastic leukemia (ALL) is the most common hematological malignancy in pediatrics, and immune‐related genes (IRGs) play crucial role in its development. Our study aimed to identify prognostic immune biomarkers of pediatric ALL and construct a risk assessment model.

Methods

Pediatric ALL patients’ gene expression data were downloaded from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. We screened differentially expressed IRGs (DEIRGs) between the relapse and non‐relapse groups. Cox regression analysis was used to identify optimal prognostic genes, then, a risk model was constructed, and its accuracy was verified in different cohorts.

Results

We screened 130 DEIRGs from 251 pediatric ALL samples. The top three pathways that DEIRGs may influence tumor progression are NABA matrisome‐associated, chemotaxis, and antimicrobial humoral response. A set of 84 prognostic DEIRGs was identified by using univariate Cox analysis. Then, Lasso regression and multivariate Cox regression analysis screened four optimal genes (PRDX2, S100A10, RORB, and SDC1), which were used to construct the prognostic risk model. The risk score was calculated and the survival analysis results showed that high‐risk score was associated with poor overall survival (OS) (p = 3.195 × 10⁻⁷). The time‐dependent survival receiver operating characteristic curves showed good prediction accuracy (Area Under Curves for 3‐year, 5‐year OS were 0.892 and 0.89, respectively). And the predictive performance of our risk model was successfully verified in testing cohort and entire cohort.

Conclusions

Our prognostic risk model can effectively divide pediatric ALL patients into high‐risk and low‐risk groups, which may help predict clinical prognosis and optimize individualized treatment.

Clinical Features and Prognosis of Merkel Cell Carcinoma in Elderly Patients

BACKGROUND Merkel cell carcinoma (MCC) occurs primarily among elderly patients over 70 years old, but the ability to predict the prognosis of these elderly patients is poor. This population-based study aimed to identify prognostic risk factors for elderly patients with MCC. MATERIAL AND METHODS The survival and disease information of MCC patients age 65 years or older was downloaded from the SEER database, and all data were split into 2 groups based on age 80 years, with overall survival and MCC-specific survival as the main outcome indicators. RESULTS Application of the inclusion criteria yielded 1973 patients with MCC, of whom 55.6% were age 65-80 years. Among them, 1258 were males, accounting for 63.8%. In survival analysis, factors that were significantly correlated with overall survival and MCC-specific survival were N stage, M stage, liver metastasis, and lymph node surgery. CONCLUSIONS We provide epidemiological insights into Merkel cell carcinoma in elderly patients and confirmed that patients receiving lymph node surgery have better outcomes. To the best of our knowledge, this is the first study to show that the occurrence of liver metastasis is associated with poor prognosis. Our results will help strengthen monitoring of the liver condition of elderly patients and to perform necessary lymph node surgery within the patient's tolerance.

Outcomes of tissue versus mechanical aortic valve replacement in patients 50 to 70 years of age

BACKGROUND

Societal guidelines suggest that aortic valve replacement (AVR) in patients age 50 to 70 years can be performed with either bioprosthetic or mechanical valves. This study reviewed outcomes between these valve types among patients aged 50 to 70 years undergoing AVR.

METHODS

We examined adult patients 50 to 70 years undergoing isolated AVR with a mechanical or bioprosthetic valve at a single institution between 2010 and 2018. Kaplan-Meier analysis was used to evaluate longitudinal survival and multivariable Cox regression analysis was used for risk adjustment. A propensity-matched analysis was performed as well.

RESULTS

A total of 723 patients underwent isolated AVR with 467 (64.6%) receiving a bioprosthetic valve. At baseline, patients undergoing bioprosthetic AVR were older (median 65 vs 60 years; P < .001). One-year survival was comparable, however, survival at 5 years was significantly higher among patients undergoing mechanical AVR (95.5% vs 82.6%; P = .010). Among the 196 matched pairs, bioprosthetic AVR was associated with an increased adjusted hazard for death (hazards ratio, 3.29; P < .001). Additionally, 5-year freedom from stroke and bleeding were similar following matching, though mechanical AVR was associated with a greater freedom from repeat valve intervention (97.5% vs 92.9%; P = .020).

CONCLUSION

In patients age 50 to 70, mechanical AVR is associated with improved long-term survival and freedom from repeat aortic valve intervention. Further large cohort studies should be performed to explore the potential benefits of mechanical valve replacement in this age range.

Causal inference in the face of competing events

Purpose of review

Epidemiologists frequently must handle competing events, which prevent the event of interest from occurring. We review considerations for handling competing events when interpreting results causally.

Recent findings

When interpreting statistical associations as causal effects, we recommend following a causal inference "roadmap" as one would in an analysis without competing events. There are, however, special considerations to be made for competing events when choosing the causal estimand that best answers the question of interest, selecting the statistical estimand (e.g. the cause-specific or subdistribution) that will target that causal estimand, and assessing whether causal identification conditions (e.g., conditional exchangeability, positivity, and consistency) have been sufficiently met.

Summary

When doing causal inference in the competing events setting, it is critical to first ascertain the relevant question and the causal estimand that best answers it, with the choice often being between estimands that do and do not eliminate competing events.

Bioinformatic screening and identification of downregulated hub genes in adrenocortical carcinoma

The molecular mechanisms of adrenocortical carcinoma (ACC) carcinogenesis and progression remain unclear. In the present study, three microarray datasets from the Gene Expression Omnibus database were screened, which identified a total of 96 differentially expressed genes (DEGs). A protein-protein interaction network (PPI) was established for these DEGs and module analysis was performed using STRING and Cytoscape. A total of eight hub genes were identified from the most significant module; namely, calponin 1 (CNN1), myosin light chain kinase (MYLK), cysteine and glycine rich protein 1 (CSRP1), myosin heavy chain 11 (MYH11), fibulin extracellular matrix protein 2 (EFEMP2), fibulin 1 (FBLN1), microfibril associated protein 4 (MFAP4) and fibulin 5 (FBLN5). The biological functions of these hub genes were analyzed using the DAVID online tool. Changes in the expression of hub genes did not affect overall survival; however, downregulated EFEMP2 decreased disease-free survival. CSRP1 and MFAP4 expression levels were associated with adverse clinicopathological features. In conclusion, although all eight hub genes were downregulated in ACC, they appeared to have important functions in ACC carcinogenesis and progression. Identification of these genes complements the genetic expression profile of ACC and provides insight for the diagnosis, treatment and prognosis of ACC.

Arteriovenous Fistula Placement, Maturation, and Patency Loss in Older Patients Initiating Hemodialysis

RATIONALE & OBJECTIVE

The current clinical guidelines for vascular access do not have specific recommendations for older hemodialysis patients. Our study aimed to determine the association of age with arteriovenous fistula (AVF) placement, maturation, and primary and secondary patency loss among older hemodialysis recipients.

STUDY DESIGN

Retrospective cohort study.

SETTING & PARTICIPANTS

A US national cohort of incident hemodialysis patients 67 years or older (N = 43,851) assembled from the US Renal Data System.

EXPOSURE

Age at dialysis initiation.

OUTCOMES

AVF placement, maturation, primary patency loss, and abandonment.

ANALYTICAL APPROACH

Cause-specific and subdistribution proportional hazards models were used to examine the association of age and AVF outcomes, with kidney transplantation, peritoneal dialysis, and death treated as competing events. Age cutoff was identified by restricted cubic splines. We compared crude and inverse probability-weighted cumulative incidence functions using Gray's test.

RESULTS

As compared with those aged 67-<77 years, patients 77 years or older had significantly lower probabilities of AVF placement (adjusted cause-specific HR [cHR], 0.96 [95% CI, 0.92-0.99]; adjusted subdistribution HR [sHR], 0.92 [95% CI, 0.89-0.95]; Gray's test P < 0.001) and maturation (adjusted cHR, 0.95 [95% CI, 0.91-0.99]; adjusted sHR, 0.93 [95% CI, 0.90-0.97]; P < 0.001). However, age was not associated with AVF primary (adjusted cHR, 1.05 [95% CI, 1.00-1.11]; adjusted sHR, 1.04 [95% CI, 0.99-1.09]; P = 0.09) or secondary (adjusted cHR, 1.06 [95% CI, 0.94-1.20]; adjusted sHR, 1.05 [95% CI, 0.93-1.18]; P = 0.4) patency loss.

LIMITATIONS

Reliance on administrative claims to ascertain AVF outcomes.

CONCLUSIONS

The likelihood of AVF maturation is an important consideration for vascular access planning. Age alone should not be the basis for excluding older dialysis patients from AVF creation because maintenance of fistula patency was not reduced with older age despite a modest reduction in fistula maturation.

The dose-response curve in cognitive-behavioral therapy for anxiety disorders

Previous studies examining the dose-response curve in psychotherapy have suggested that 11-19 sessions may be necessary for at least 50% of individuals to show clinically significant improvement. However, this curve has not been examined specifically for cognitive-behavioral therapy (CBT) for anxiety disorders, for which a more rapid recovery curve may be expected. Survival analysis was used to assess the dose-response curve for 201 patients with anxiety disorders who received weekly CBT at an anxiety specialty clinic. The primary outcome measure was the Outcome Questionnaire-45.2, which patients completed prior to each treatment session. Sixty-four percent of the sample achieved reliable change, and this response occurred in approximately five sessions on average. Fifty percent of the sample achieved clinically significant improvement, which occurred in approximately eight sessions on average. The findings suggest that earlier response may be expected in CBT for anxiety disorders, and are discussed in terms of potential ways to further improve response rates for this treatment.

OSlgg: An Online Prognostic Biomarker Analysis Tool for Low-Grade Glioma

Glioma is the most frequent primary brain tumor that causes high mortality and morbidity with poor prognosis. There are four grades of gliomas, I to IV, among which grade II and III are low-grade glioma (LGG). Although less aggressive, LGG almost universally progresses to high-grade glioma and eventual causes death if lacking of intervention. Current LGG treatment mainly depends on surgical resection followed by radiotherapy and chemotherapy, but the survival rates of LGG patients are low. Therefore, it is necessary to use prognostic biomarkers to classify patients into subgroups with different risks and guide clinical managements. Using gene expression profiling and long-term follow-up data, we established an Online consensus Survival analysis tool for LGG named OSlgg. OSlgg is comprised of 720 LGG cases from two independent cohorts. To evaluate the prognostic potency of genes, OSlgg employs the Kaplan-Meier plot with hazard ratio and p value to assess the prognostic significance of genes of interest. The reliability of OSlgg was verified by analyzing 86 previously published prognostic biomarkers of LGG. Using OSlgg, we discovered two novel potential prognostic biomarkers (CD302 and FABP5) of LGG, and patients with the elevated expression of either CD302 or FABP5 present the unfavorable survival outcome. These two genes may be novel risk predictors for LGG patients after further validation. OSlgg is public and free to the users at http://bioinfo.henu.edu.cn/LGG/LGGList.jsp.

Parametric g-formula implementations for causal survival analyses

The g-formula can be used to estimate the survival curve under a sustained treatment strategy. Two available estimators of the g-formula are noniterative conditional expectation and iterative conditional expectation. We propose a version of the iterative conditional expectation estimator and describe its procedures for deterministic and random treatment strategies. Also, because little is known about the comparative performance of noniterative and iterative conditional expectation estimators, we explore their relative efficiency via simulation studies. Our simulations show that, in the absence of model misspecification and unmeasured confounding, our proposed iterative conditional expectation estimator and the noniterative conditional expectation estimator are similarly efficient, and that both are at least as efficient as the classical iterative conditional expectation estimator. We describe an application of both noniterative and iterative conditional expectation to answer "when to start" treatment questions using data from the HIV-CAUSAL Collaboration.

Machine-Learning Approaches in COVID-19 Survival Analysis and Discharge-Time Likelihood Prediction Using Clinical Data

As a highly contagious respiratory disease, COVID-19 has yielded high mortality rates since its emergence in December 2019. As the number of COVID-19 cases soars in epicenters, health officials are warning about the possibility of the designated treatment centers being overwhelmed by coronavirus patients. In this study, several computational techniques are implemented to analyze the survival characteristics of 1,182 patients. The computational results agree with the outcome reported in early clinical reports released for a group of patients from China that confirmed a higher mortality rate in men compared with women and in older age groups. The discharge-time prediction of COVID-19 patients was also evaluated using different machine-learning and statistical analysis methods. The results indicate that the Gradient Boosting survival model outperforms other models for patient survival prediction in this study. This research study is aimed to help health officials make more educated decisions during the outbreak.

Potential Added Value of PET/CT Radiomics for Survival Prognostication beyond AJCC 8th Edition Staging in Oropharyngeal Squamous Cell Carcinoma

Accurate risk-stratification can facilitate precision therapy in oropharyngeal squamous cell carcinoma (OPSCC). We explored the potential added value of baseline positron emission tomography (PET)/computed tomography (CT) radiomic features for prognostication and risk stratification of OPSCC beyond the American Joint Committee on Cancer (AJCC) 8th edition staging scheme. Using institutional and publicly available datasets, we included OPSCC patients with known human papillomavirus (HPV) status, without baseline distant metastasis and treated with curative intent. We extracted 1037 PET and 1037 CT radiomic features quantifying lesion shape, imaging intensity, and texture patterns from primary tumors and metastatic cervical lymph nodes. Utilizing random forest algorithms, we devised novel machine-learning models for OPSCC progression-free survival (PFS) and overall survival (OS) using “radiomics” features, “AJCC” variables, and the “combined” set as input. We designed both single- (PET or CT) and combined-modality (PET/CT) models. Harrell’s C-index quantified survival model performance; risk stratification was evaluated in Kaplan–Meier analysis. A total of 311 patients were included. In HPV-associated OPSCC, the best “radiomics” model achieved an average C-index ± standard deviation of 0.62 ± 0.05 (p = 0.02) for PFS prediction, compared to 0.54 ± 0.06 (p = 0.32) utilizing “AJCC” variables. Radiomics-based risk-stratification of HPV-associated OPSCC was significant for PFS and OS. Similar trends were observed in HPV-negative OPSCC. In conclusion, radiomics imaging features extracted from pre-treatment PET/CT may provide complimentary information to the current AJCC staging scheme for survival prognostication and risk-stratification of HPV-associated OPSCC.