ResearchPad - Cancer Research https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Efficacy of adjuvant chemotherapy with S-1 in stage II oral squamous cell carcinoma patients: A comparative study using the propensity score matching method]]> https://www.researchpad.co/product?articleinfo=N83ad1f15-cdbb-4f4c-8d9c-388a45a97cce

It has been reported that 20% of early-stage oral squamous cell carcinoma (OSCC) patients treated with surgery alone (SA) may exhibit postoperative relapse within 2–3 years and have poor prognoses. We aimed to determine the safety of S-1 adjuvant chemotherapy and the potential differences in the disease-free survival (DFS) between patients with T2N0 (stage II) OSCC treated with S-1 adjuvant therapy (S-1) and those treated with SA. This single-center retrospective cohort study was conducted at Kumamoto University, between April 2004 and March 2012, and included 95 patients with stage II OSCC. The overall cohort (OC), and propensity score-matched cohort (PSMC) were analyzed. In the OC, 71 and 24 patients received SA and S-1, respectively. The time to relapse (TTR), DFS, and overall survival were better in the S-1 group, but the difference was not significant. In the PSMC, 20 patients each received SA and S-1. The TTR was significantly lower in the S-1 group than in the SA group, while the DFS was significantly improved in the former. S-1 adjuvant chemotherapy may be more effective than SA in early-stage OSCC.

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<![CDATA[SlicerDMRI: Diffusion MRI and Tractography Research Software for Brain Cancer Surgery Planning and Visualization]]> https://www.researchpad.co/product?articleinfo=N5117ff89-1cc2-489b-9f6c-323db140a822

PURPOSE

We present SlicerDMRI, an open-source software suite that enables research using diffusion magnetic resonance imaging (dMRI), the only modality that can map the white matter connections of the living human brain. SlicerDMRI enables analysis and visualization of dMRI data and is aimed at the needs of clinical research users. SlicerDMRI is built upon and deeply integrated with 3D Slicer, a National Institutes of Health–supported open-source platform for medical image informatics, image processing, and three-dimensional visualization. Integration with 3D Slicer provides many features of interest to cancer researchers, such as real-time integration with neuronavigation equipment, intraoperative imaging modalities, and multimodal data fusion. One key application of SlicerDMRI is in neurosurgery research, where brain mapping using dMRI can provide patient-specific maps of critical brain connections as well as insight into the tissue microstructure that surrounds brain tumors.

PATIENTS AND METHODS

In this article, we focus on a demonstration of SlicerDMRI as an informatics tool to enable end-to-end dMRI analyses in two retrospective imaging data sets from patients with high-grade glioma. Analyses demonstrated here include conventional diffusion tensor analysis, advanced multifiber tractography, automated identification of critical fiber tracts, and integration of multimodal imagery with dMRI.

RESULTS

We illustrate the ability of SlicerDMRI to perform both conventional and advanced dMRI analyses as well as to enable multimodal image analysis and visualization. We provide an overview of the clinical rationale for each analysis along with pointers to the SlicerDMRI tools used in each.

CONCLUSION

SlicerDMRI provides open-source and clinician-accessible research software tools for dMRI analysis. SlicerDMRI is available for easy automated installation through the 3D Slicer Extension Manager.

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<![CDATA[CIViCpy: A Python Software Development and Analysis Toolkit for the CIViC Knowledgebase]]> https://www.researchpad.co/product?articleinfo=N2b318ddc-a380-44cd-9624-77c382823503

PURPOSE

Precision oncology depends on the matching of tumor variants to relevant knowledge describing the clinical significance of those variants. We recently developed the Clinical Interpretations for Variants in Cancer (CIViC; civicdb.org) crowd-sourced, expert-moderated, and open-access knowledgebase. CIViC provides a structured framework for evaluating genomic variants of various types (eg, fusions, single-nucleotide variants) for their therapeutic, prognostic, predisposing, diagnostic, or functional utility. CIViC has a documented application programming interface for accessing CIViC records: assertions, evidence, variants, and genes. Third-party tools that analyze or access the contents of this knowledgebase programmatically must leverage this application programming interface, often reimplementing redundant functionality in the pursuit of common analysis tasks that are beyond the scope of the CIViC Web application.

METHODS

To address this limitation, we developed CIViCpy (civicpy.org), a software development kit for extracting and analyzing the contents of the CIViC knowledgebase. CIViCpy enables users to query CIViC content as dynamic objects in Python. We assess the viability of CIViCpy as a tool for advancing individualized patient care by using it to systematically match CIViC evidence to observed variants in patient cancer samples.

RESULTS

We used CIViCpy to evaluate variants from 59,437 sequenced tumors of the American Association for Cancer Research Project GENIE data set. We demonstrate that CIViCpy enables annotation of > 1,200 variants per second, resulting in precise variant matches to CIViC level A (professional guideline) or B (clinical trial) evidence for 38.6% of tumors.

CONCLUSION

The clinical interpretation of genomic variants in cancers requires high-throughput tools for interoperability and analysis of variant interpretation knowledge. These needs are met by CIViCpy, a software development kit for downstream applications and rapid analysis. CIViCpy is fully documented, open-source, and available free online.

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<![CDATA[Integrated Informatics Analysis of Cancer-Related Variants]]> https://www.researchpad.co/product?articleinfo=N63eb3b07-012f-4300-8a0f-2ebaece9b518

PURPOSE

The modern researcher is confronted with hundreds of published methods to interpret genetic variants. There are databases of genes and variants, phenotype-genotype relationships, algorithms that score and rank genes, and in silico variant effect prediction tools. Because variant prioritization is a multifactorial problem, a welcome development in the field has been the emergence of decision support frameworks, which make it easier to integrate multiple resources in an interactive environment. Current decision support frameworks are typically limited by closed proprietary architectures, access to a restricted set of tools, lack of customizability, Web dependencies that expose protected data, or limited scalability.

METHODS

We present the Open Custom Ranked Analysis of Variants Toolkit1 (OpenCRAVAT) a new open-source, scalable decision support system for variant and gene prioritization. We have designed the resource catalog to be open and modular to maximize community and developer involvement, and as a result, the catalog is being actively developed and growing every month. Resources made available via the store are well suited for analysis of cancer, as well as Mendelian and complex diseases.

RESULTS

OpenCRAVAT offers both command-line utility and dynamic graphical user interface, allowing users to install with a single command, easily download tools from an extensive resource catalog, create customized pipelines, and explore results in a richly detailed viewing environment. We present several case studies to illustrate the design of custom workflows to prioritize genes and variants.

CONCLUSION

OpenCRAVAT is distinguished from similar tools by its capabilities to access and integrate an unprecedented amount of diverse data resources and computational prediction methods, which span germline, somatic, common, rare, coding, and noncoding variants.

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<![CDATA[Developing an FHIR-Based Computational Pipeline for Automatic Population of Case Report Forms for Colorectal Cancer Clinical Trials Using Electronic Health Records]]> https://www.researchpad.co/product?articleinfo=Ncc99f19c-a654-4ff9-b4a2-cbfef96ce508

PURPOSE

The Fast Healthcare Interoperability Resources (FHIR) is emerging as a next-generation standards framework developed by HL7 for exchanging electronic health care data. The modeling capability of FHIR in standardizing cancer data has been gaining increasing attention by the cancer research informatics community. However, few studies have been conducted to examine the capability of FHIR in electronic data capture (EDC) applications for effective cancer clinical trials. The objective of this study was to design, develop, and evaluate an FHIR-based method that enables the automation of the case report forms (CRFs) population for cancer clinical trials using real-world electronic health records (EHRs).

MATERIALS AND METHODS

We developed an FHIR-based computational pipeline of EDC with a case study for modeling colorectal cancer trials. We first leveraged an existing FHIR-based cancer profile to represent EHR data of patients with colorectal cancer, and then we used the FHIR Questionnaire and QuestionnaireResponse resources to represent the CRFs and their data population. To test the accuracy of and overall quality of the computational pipeline, we used synoptic reports of 287 Mayo Clinic patients with colorectal cancer from 2013 to 2019 with standard measures of precision, recall, and F1 score.

RESULTS

Using the computational pipeline, a total of 1,037 synoptic reports were successfully converted as the instances of the FHIR-based cancer profile. The average accuracy for converting all data elements (excluding tumor perforation) of the cancer profile was 0.99, using 200 randomly selected records. The average F1 score for populating nine questions of the CRFs in a real-world colorectal cancer trial was 0.95, using 100 randomly selected records.

CONCLUSION

We demonstrated that it is feasible to populate CRFs with EHR data in an automated manner with satisfactory performance. The outcome of the study provides helpful insight into future directions in implementing FHIR-based EDC applications for modern cancer clinical trials.

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<![CDATA[MLCD: A Unified Software Package for Cancer Diagnosis]]> https://www.researchpad.co/product?articleinfo=N848b0810-ca6e-4a57-b2d2-f63dea367409

PURPOSE

Machine Learning Package for Cancer Diagnosis (MLCD) is the result of a National Institutes of Health/National Cancer Institute (NIH/NCI)-sponsored project for developing a unified software package from state-of-the-art breast cancer biopsy diagnosis and machine learning algorithms that can improve the quality of both clinical practice and ongoing research.

METHODS

Whole-slide images of 240 well-characterized breast biopsy cases, initially assembled under R01 CA140560, were used for developing the algorithms and training the machine learning models. This software package is based on the methodology developed and published under our recent NIH/NCI-sponsored research grant (R01 CA172343) for finding regions of interest (ROIs) in whole-slide breast biopsy images, for segmenting ROIs into histopathologic tissue types and for using this segmentation in classifiers that can suggest final diagnoses.

RESULT

The package provides an ROI detector for whole-slide images and modules for semantic segmentation into tissue classes and diagnostic classification into 4 classes (benign, atypia, ductal carcinoma in situ, invasive cancer) of the ROIs. It is available through the GitHub repository under the Massachusetts Institute of Technology license and will later be distributed with the Pathology Image Informatics Platform system. A Web page provides instructions for use.

CONCLUSION

Our tools have the potential to provide help to other cancer researchers and, ultimately, to practicing physicians and will motivate future research in this field. This article describes the methodology behind the software development and gives sample outputs to guide those interested in using this package.

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<![CDATA[Cancer Imaging Phenomics via CaPTk: Multi-Institutional Prediction of Progression-Free Survival and Pattern of Recurrence in Glioblastoma]]> https://www.researchpad.co/product?articleinfo=N4aa69618-fc33-4b62-bf4f-a48f14d8d52f

PURPOSE

To construct a multi-institutional radiomic model that supports upfront prediction of progression-free survival (PFS) and recurrence pattern (RP) in patients diagnosed with glioblastoma multiforme (GBM) at the time of initial diagnosis.

PATIENTS AND METHODS

We retrospectively identified data for patients with newly diagnosed GBM from two institutions (institution 1, n = 65; institution 2, n = 15) who underwent gross total resection followed by standard adjuvant chemoradiation therapy, with pathologically confirmed recurrence, sufficient follow-up magnetic resonance imaging (MRI) scans to reliably determine PFS, and available presurgical multiparametric MRI (MP-MRI). The advanced software suite Cancer Imaging Phenomics Toolkit (CaPTk) was leveraged to analyze standard clinical brain MP-MRI scans. A rich set of imaging features was extracted from the MP-MRI scans acquired before the initial resection and was integrated into two distinct imaging signatures for predicting mean shorter or longer PFS and near or distant RP. The predictive signatures for PFS and RP were evaluated on the basis of different classification schemes: single-institutional analysis, multi-institutional analysis with random partitioning of the data into discovery and replication cohorts, and multi-institutional assessment with data from institution 1 as the discovery cohort and data from institution 2 as the replication cohort.

RESULTS

These predictors achieved cross-validated classification performance (ie, area under the receiver operating characteristic curve) of 0.88 (single-institution analysis) and 0.82 to 0.83 (multi-institution analysis) for prediction of PFS and 0.88 (single-institution analysis) and 0.56 to 0.71 (multi-institution analysis) for prediction of RP.

CONCLUSION

Imaging signatures of presurgical MP-MRI scans reveal relatively high predictability of time and location of GBM recurrence, subject to the patients receiving standard first-line chemoradiation therapy. Through its graphical user interface, CaPTk offers easy accessibility to advanced computational algorithms for deriving imaging signatures predictive of clinical outcome and could similarly be used for a variety of radiomic and radiogenomic analyses.

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<![CDATA[OncoMX: A Knowledgebase for Exploring Cancer Biomarkers in the Context of Related Cancer and Healthy Data]]> https://www.researchpad.co/product?articleinfo=N462bd4a0-032c-4efa-9990-c71ccbd2af6a

PURPOSE

The purpose of OncoMX1 knowledgebase development was to integrate cancer biomarker and relevant data types into a meta-portal, enabling the research of cancer biomarkers side by side with other pertinent multidimensional data types.

METHODS

Cancer mutation, cancer differential expression, cancer expression specificity, healthy gene expression from human and mouse, literature mining for cancer mutation and cancer expression, and biomarker data were integrated, unified by relevant biomedical ontologies, and subjected to rule-based automated quality control before ingestion into the database.

RESULTS

OncoMX provides integrated data encompassing more than 1,000 unique biomarker entries (939 from the Early Detection Research Network [EDRN] and 96 from the US Food and Drug Administration) mapped to 20,576 genes that have either mutation or differential expression in cancer. Sentences reporting mutation or differential expression in cancer were extracted from more than 40,000 publications, and healthy gene expression data with samples mapped to organs are available for both human genes and their mouse orthologs.

CONCLUSION

OncoMX has prioritized user feedback as a means of guiding development priorities. By mapping to and integrating data from several cancer genomics resources, it is hoped that OncoMX will foster a dynamic engagement between bioinformaticians and cancer biomarker researchers. This engagement should culminate in a community resource that substantially improves the ability and efficiency of exploring cancer biomarker data and related multidimensional data.

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<![CDATA[Patterns of distant metastases in 215 Merkel cell carcinoma patients: Implications for prognosis and surveillance]]> https://www.researchpad.co/product?articleinfo=N3f9ae47c-26e5-4c31-b2f8-88bfc0a2f7bc

Abstract

Approximately one‐third of Merkel cell carcinoma (MCC) patients eventually develop distant metastatic disease. Little is known about whether the location of the primary lesion is predictive of initial distant metastatic site, or if survival likelihood differs depending on the metastatic site. Such data could inform imaging/surveillance practices and improve prognostic accuracy. Multivariate and competing‐risk analyses were performed on a cohort of 215 MCC patients with distant metastases, 31% of whom had two or more initial sites of distant metastasis. At time of initial distant metastasis in the 215 patients, metastatic sites (n = 305) included non‐regional lymph nodes (present in 41% of patients), skin/body wall (25%), liver (23%), bone (21%), pancreas (8%), lung (7%), and brain (5%). Among the 194 patients who presented with MCC limited to local or regional sites (stage I‐III) but who ultimately developed distant metastases, distant progression occurred in 49% by 1 year and in 80% by 2 years following initial diagnosis. Primary MCC locations differed in how likely they were to metastasize to specific organs/sites (P < .001). For example, liver metastases were far more likely from a head/neck primary (43% of 58 patients) versus a lower limb primary (5% of 39 patients; < .0001). Skin‐only distant metastasis was associated with lower MCC‐specific mortality as compared to metastases in multiple organs/sites (HR 2.7; P = .003), in the liver (HR 2.1; P = .05), or in distant lymph nodes (HR 2.0; P = .045). These data reflect outcomes before PD1‐pathway inhibitor availability, which may positively impact survival. In conclusion, primary MCC location is associated with a pattern of distant spread, which may assist in optimizing surveillance. Because it is linked to survival, the site of initial distant metastasis should be considered when assessing prognosis.

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<![CDATA[Biguanides in combination with olaparib limits tumorigenesis of drug‐resistant ovarian cancer cells through inhibition of Snail]]> https://www.researchpad.co/product?articleinfo=N3f109a5a-c2dd-4a7b-bd68-18fc657ab139

Abstract

Ovarian cancer is the most lethal gynecological malignancy. Currently, new chemotherapeutic strategies are required to improve patient outcome and survival. Biguanides, classic anti‐diabetic drugs, have gained importance for theiri antitumor potency demonstrated by various studies. Olaparib is a PARP inhibitor approved for maintenance therapy following platinum‐based chemotherapy. Furthermore, Snai1, a transcription factor that works as a master regulator of the epithelial/mesenchymal transition process (EMT) is involved in ovarian cancer resistance and progression. Here we aimed to demonstrate the possible cross talk between biguanides and Snail in response to olaparib combination therapy. In this study, we have shown that while in A2780CR cells biguanides reduced cell survival (single treatments ~20%; combined treatment ~44%) and cell migration (single treatments ~45%; biguanide‐olaparib ~80%) significantly, A2780PAR exhibited superior efficacy with single (~60%) and combined treatments (~80%). Moreover, our results indicate that knock‐down of Snail further enhances the attenuation of migration, inhibits EMT related‐proteins (~90%) and induces a synergistic effect in biguanide‐olaparib treatment. Altogether, this work suggests a novel treatment strategy against drug‐resistant or recurrent ovarian cancer.

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<![CDATA[A nomogram to predict outcomes of lung cancer patients after pneumonectomy based on 47 indicators]]> https://www.researchpad.co/product?articleinfo=N1de99cde-1ca5-446d-83c4-3697687d547c

Abstract

Aims

We aimed to establish a nomogram for lung cancer using patients' characteristics and potential hematological biomarkers.

Methods

Principle component analysis was used to reduce the dimensions of the data, and each component was transformed into categorical variables based on cutoff values obtained using the X‐tile software. Multivariate analysis was used to determine potential prognostic biomarkers. Five components were used in the predictive nomogram. Internal validation of the model was performed by bootstrapping of samples, while external validation was performed on a separate cohort from Shandong Cancer Hospital. The predictive accuracy of the model was measured by concordance index and risk group stratification. Decision curve analysis was performed to evaluate the net benefit of the models.

Results

One hundred patients in the Discovery group and 111 patients in the Validation group were retrospectively analyzed in this study. Forty‐seven indexes were sorted into eight subgroups. Five components based on cox regression analysis were enrolled into the predictive nomogram. The nomogram prediction of the probability of 3‐ and 5‐year overall survival was in great concordance with the actual observations. Of interest, the nomogram allowed better risk stratification of patients and better accuracy in predicting patients' survival compared with pathological tumor‐node‐metastasis staging system.

Conclusion

A nomogram was established for prognosis of lung cancer, which can be used for treatment selection and clinical care management.

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<![CDATA[Significance of concurrent use of weekly cisplatin in carbon‐ion radiotherapy for locally advanced adenocarcinoma of the uterine cervix: A propensity score‐matched analysis]]> https://www.researchpad.co/product?articleinfo=Nfc582835-4783-418a-95fe-5a3d34adea73

Abstract

Background

Although carbon‐ion radiotherapy (C‐ion RT) with concurrent chemotherapy (chemo‐C‐ion RT) is a promising treatment for adenocarcinoma (AC) of the uterine cervix, its long‐term efficacy remains unclear. We evaluated the long‐term significance of concurrent weekly cisplatin and C‐ion RT for locally advanced AC of the uterine cervix.

Methods

We performed a pooled analysis of patients with stage IIB–IVA AC of the uterine cervix who underwent C‐ion RT alone or chemo‐C‐ion RT between September 2007 and December 2018 at our institution. Patients received 74.4 Gy (relative biological effectiveness) with or without cisplatin (40 mg/m2 per week for up to 5 weeks), underwent no prior pelvic RT or systemic therapy, and had a performance status of 0‐2. Propensity score matching was based on the year of diagnosis, regional lymph node metastasis, and stage.

Results

The matched cohort contained 26 patients who underwent C‐ion RT and 26 who underwent chemo‐C‐ion RT. The median age and follow‐up period were 57 (range, 28‐79) years and 34 (range, 2‐126) months, respectively. The 5‐year overall survival rate was significantly better in the chemo‐C‐ion RT group (72%) than in the C‐ion RT group (46%; P = .041). The 5‐year distant metastatic‐free rate was also significantly better in the chemo‐C‐ion RT group (66%) than in the C‐ion RT group (41%; P = .048). The incidence of grade ≥ 3 late toxicities was comparable between the two groups.

Conclusions

Chemo‐C‐ion RT for locally advanced AC of the uterine cervix is associated with a long‐term survival benefit.

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<![CDATA[Nanoparticle albumin‐bound paclitaxel in elder patients with advanced squamous non‐small‐cell lung cancer: A retrospective study]]> https://www.researchpad.co/product?articleinfo=N6f02d988-6f5f-4be6-a9a8-e0d0246f8f6c

Abstract

Purpose

This study aimed to assess the effect of nanoparticle albumin‐bound paclitaxel (nab‐PTX) chemotherapy regimens in elderly patients (≥70 years old) with advanced squamous non‐small‐cell lung cancer (NSCLC).

Patients and Methods

The clinical records of elderly patients aged ≥70 years with advanced squamous NSCLC were reviewed retrospectively. All of these patients received nab‐PTX, with or without combination of chemotherapy in Shandong Cancer Hospital and Institute between 1 July 2012 and 30 June 2017. We analyzed the toxicity profiles, progression‐free survival (PFS), overall survival (OS), objective response rate (ORR), and disease control rate (DCR).

Results

Totally, 52 elderly patients with squamous NSCLC were included in the analysis. For all patients, the ORR was 34.6%, the DCR was 80.8%, median PFS was 5.9 months (95% confidence interval [CI]: 4.0‐7.8 months), and median OS was 14.3 months (95% CI: 11.0‐17.8 months). Combination with chemotherapy significantly prolonged OS (19.3 vs 11.2 months, P = .016), despite a nonsignificant improvement in PFS (7.1 vs 4.2 months, P = .060) vs monotherapy. For patients who received nab‐PTX as first‐line treatment, the median PFS and OS were 6.7 months and 17.2 months, respectively, and the median OS in combination therapy subgroup was significantly higher than that in monotherapy group (20.3 vs 11.2 months, P = .013). Meanwhile, the median PFS and OS of patients with nab‐PTX as second‐ or later‐line treatment were 4.4 months and 13.3 months, respectively, but no survival benefit was achieved by the combination chemotherapy when compared with single‐agent chemotherapy. Hematologic toxicities were the most common adverse events (AEs), which include grade 3 or 4 neutropenia (13.7%), thrombocytopenia (4.1%), and anemia (6.8%). The main nonhematologic toxicities were peripheral sensory neuropathy (39.7%), followed by anorexia and nausea/vomiting.

Conclusion

In elderly advanced squamous NSCLC patients, the treatment of nab‐PTX was effective and well tolerated.

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<![CDATA[High serum PD‐L1 level is a poor prognostic biomarker in surgically treated esophageal cancer]]> https://www.researchpad.co/product?articleinfo=Ne3a266a0-5616-4696-b817-57bdf47dfa05

Abstract

Background

Programmed death ligand 1 (PD‐L1) inhibitor has been approved as one of the standard therapies for various cancers. Some reports have shown that serum PD‐L1 level is associated with advanced tumor stages and poor prognosis; however, corresponding pathological information in esophageal cancer patients is lacking. Therefore, we evaluated the clinicopathological and prognostic impact of serum PD‐L1 levels in surgically treated esophageal cancer.

Methods

A total of 150 patients who underwent radical resection for esophageal cancer were included in the study. Preoperative serum PD‐L1 levels were analyzed using the enzyme‐linked immunosorbent assay kit. A cutoff level of 65.6 pg/mL was used to divide the patients into two groups, and univariate and multivariate analyses were conducted to compare the clinicopathological characteristics and prognoses between these two groups.

Results

Although significant associations between serum PD‐L1 levels and clinicopathological variables were observed, serum PD‐L1 level was significantly associated with high neutrophil counts, high CRP levels, low albumin levels, and high squamous cell carcinoma antigen levels. Furthermore, serum PD‐L1 level was associated with poor overall survival independent to TNM factors.

Conclusions

High preoperative level of serum PD‐L1 is a prognostic factor for poor overall survival in patients with surgically treated esophageal cancer.

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<![CDATA[Developing a cancer‐specific trigger tool to identify treatment‐related adverse events using administrative data]]> https://www.researchpad.co/product?articleinfo=N725b53e3-60c8-4ed5-bb78-f263db60a707

Abstract

Background

As there are few validated tools to identify treatment‐related adverse events across cancer care settings, we sought to develop oncology‐specific “triggers” to flag potential adverse events among cancer patients using claims data.

Methods

322 887 adult patients undergoing an initial course of cancer‐directed therapy for breast, colorectal, lung, or prostate cancer from 2008 to 2014 were drawn from a large commercial claims database. We defined 16 oncology‐specific triggers using diagnosis and procedure codes. To distinguish treatment‐related complications from comorbidities, we required a logical and temporal relationship between a treatment and the associated trigger. We tabulated the prevalence of triggers by cancer type and metastatic status during 1‐year of follow‐up, and examined cancer trigger risk factors.

Results

Cancer‐specific trigger events affected 19% of patients over the initial treatment year. The trigger burden varied by disease and metastatic status, from 6% of patients with nonmetastatic prostate cancer to 41% and 50% of those with metastatic colorectal and lung cancers, respectively. The most prevalent triggers were abnormal serum bicarbonate, blood transfusion, non‐contrast chest CT scan following radiation therapy, and hypoxemia. Among patients with metastatic disease, 10% had one trigger event and 29% had two or more. Triggers were more common among older patients, women, non‐whites, patients with low family incomes, and those without a college education.

Conclusions

Oncology‐specific triggers offer a promising method for identifying potential patient safety events among patients across cancer care settings.

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<![CDATA[Survival of stage II nasopharyngeal carcinoma patients with or without concurrent chemotherapy: A propensity score matching study]]> https://www.researchpad.co/product?articleinfo=Nddfcb2bf-b012-4f8a-b2b3-d23a56ab9dac

Abstract

Background

To ascertain if concurrent chemotherapy (CCT) benefits people with stage II nasopharyngeal carcinoma (NPC) treated with two‐dimensional radiotherapy (2DRT) or intensity‐modulated radiotherapy (IMRT).

Methods

A total of 4157 patients diagnosed with stage II NPC were evaluated. Patients received radiotherapy (RT) with/without CCT. Patients were divided into 2DRT and IMRT subgroups. After propensity score matching, the role of CCT was explored in these two subgroups. Overall survival (OS) was the primary endpoint and progression‐free survival (PFS), locoregional relapse‐free survival (LRFS) and distant metastasis‐free survival (DMFS) were secondary endpoints.

Results

In the 2DRT subgroup, CCT addition to RT benefited cases with T1N1/T2N1 in OS, PFS and LRFS (P < .001, P = .003 and P = .003, respectively) significantly, but no difference was observed in patients with T2N0. DMFS were similar in the two arms. CCT was a significant protective factor for OS, PFS, and LRFS for patients with stage N1. In the IMRT subgroup, RT alone could maintain equivalent OS, PFS, LRFS and DMFS (P = .209, .448, .477 and .602 respectively) and cause less acute toxicity compared with concurrent chemoradiotherapy (CCRT).

Conclusion

CCRT was better than 2DRT alone among patients with T1‐2N1M0 stage. CCT application for NPC patients receiving IMRT led to no survival benefit and greater toxic effects.

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<![CDATA[Comparison of the biomarkers for targeted therapies in primary extra‐mammary and mammary Paget's disease]]> https://www.researchpad.co/product?articleinfo=N31631781-3797-43f8-8169-eab8eee01ff3

Abstract

Background

Primary Extra‐mammary Paget's disease (EMPD) is a very rare cutaneous adenocarcinoma affecting anogenital or axillary regions. It is characterized by a prolonged course with recurrences and eventually distant metastatic spread for which no specific therapy is known.

Methods

Eighteen EMPD (13 vulvar and five scrotal) and ten mammary Paget's disease (MPD) cases were comprehensively profiled for gene mutations, fusions and copy number alterations, and for therapy‐relevant protein biomarkers).

Results

Mutations in TP53 and PIK3CA were the most frequent in both cohorts: 7/15 and 5/15 in EMPD; 1/6 and 4/7 in MPD HER2 gene amplification was detected in 4/18 EMPD (3 vulvar and 1 scrotal case) in contrast to MPD where it was detected in the majority (7/8) of cases. TOP2A gene amplification was seen in 2/12 EMPD and 1/6 MPD, respectively. Similarly, no difference in estrogen receptor expression was seen between the EMPD (4/15) and MPD (3/10). Androgen receptor was also expressed in the majority of both cohorts (12/16 EMPD) and (7/8 MPD).Here ARv7 splice variant was detected in 1/7 EMPD and 1/4 MPD cases, respectively. PD‐L1 expression on immune cells was exclusively observed in three vulvar EMPD. In contrast to MPD, six EMPDs harbored a “high” tumor mutation burden (≥10 mutations/Mb). All tested cases from both cohorts were MSI stable.

Conclusions

EMPD shares some targetable biomarkers with its mammary counterpart (steroid receptors, PIK3CA signaling pathways, TOP2A amplification). HER2 positivity is notably lower in EMPD while biomarkers to immune checkpoint inhibitors (high TMB and PD‐L1) were observed in some EMPD. Given that no consistent molecular alteration characterizes EMPD, comprehensive theranostic profiling is required to identify individual patients with targetable molecular alterations.

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<![CDATA[Nomogram based on inflammatory indices for differentiating intrahepatic cholangiocarcinoma from hepatocellular carcinoma]]> https://www.researchpad.co/product?articleinfo=Ne19eb3ee-655d-4948-b368-0c6ade9f6c7b

Abstract

Objective

To establish nomogram based on inflammatory indices for differentiating intrahepatic cholangiocarcinoma (ICC) from hepatocellular carcinoma (HCC).

Methods

A cohort of 422 patients with HCC or ICC hospitalized at Xiangya Hospital between January 2014 and December 2018 was included in the study. Univariate and multivariate analysis was performed to identify the independent differential factors. Through combining these independent differential factors, a nomogram was established for differential diagnosis between ICC and HCC. The accuracy of nomogram was evaluated by using receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). The results were validated using a prospective study on 98 consecutive patients operated on from January 2019 to November 2019 at the same institution.

Results

Sex (OR = 9.001, 95% CI: 3.268‐24.792, P < .001), hepatitis (OR = 0.323, 95% CI: 0.121‐0.860, P = .024), alpha‐fetoprotein (AFP) (OR = 0.997, 95% CI: 0.995‐1.000, P = .046), carbohydrate antigen 19‐9 (CA199) (OR = 1.016, 95% CI: 1.007‐1.025, P < .001), and aspartate transaminase‐to‐neutrophil ratio index (ANRI) (OR = 0.904, 95% CI: 0.843‐0.969, P = .004) were the independent differential factors for ICC. Nomogram was established with well‐fitted calibration curves through incorporating these 5 factors. Comparing model 1 including gender, hepatitis, AFP, and CA199 (C index = 0.903, 95% CI: 0.849‐0.957) and model 2 enrolling AFP and CA199 (C index = 0.850, 95% CI: 0.791‐0.908), the nomogram showed a better discrimination between ICC and HCC, with a C index of 0.920 (95% CI, 0.872‐0.968). The results were consistent in the validation cohort. DCA also confirmed the conclusion.

Conclusion

A nomogram was established for the differential diagnosis between ICC and HCC preoperatively, and better therapeutic choice would be made if it was applied in clinical practice.

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<![CDATA[Landscape of distant metastasis mode and current chemotherapy efficacy of the advanced biliary tract cancer in the United States, 2010‐2016]]> https://www.researchpad.co/product?articleinfo=N2c0da61a-2597-4935-a0a3-05b990e7aef9

Abstract

Background

The distant metastasis (DM) mode and treatment efficacies in the advanced biliary tract cancer (BTC) were obscure, and a credible evaluation is urgently needed.

Method

A total of 6348 advanced BTC patients (ICC, intrahepatic cholangiocarcinoma, n = 1762; PHCC, perihilar cholangiocarcinoma, n = 1103; GBC, gallbladder cancer, n = 2580; DCC, distal cholangiocarcinoma, n = 538; AVC, carcinoma of Vater ampulla, n = 365) were enrolled from the Surveillance, Epidemiology, and End Results (SEER) database. Propensity score matching (PSM) process was carried out for less bias.

Result

The proportion of M1 patients in each subtype at first diagnosis was 26.4% (ICC), 37.2% (PHCC), 41. 0% (GBC), 24.5% (DCC), and 12.7% (AVC), and the constitution of DM sites in different subtypes varied apparently. Moreover, the survival of metastasis sites was different (P < .05 in all the subtypes) where the multi‐metastasis and distant lymph node (dLN) only always indicated the worst and best prognosis, respectively. Chemotherapy presented the most significant survival impact with the lowest hazard ratio by multivariate cox model and still provided a survival improvement after PSM (all P < .001) in all subtypes. However, the median months manifested different between patients with and without chemotherapy among the subtypes (ICC, from 5 to 9; PHCC, from 6 to 10; AVC, from 4 to 9; GBC, from 6 to 7; DCC from 6 to 8).

Conclusion

We provided a landscape about the detailed DM mode of the advanced BTC in a large population, found the survival differences among DM sites, and revealed the different chemotherapy efficacies in the BTC subtypes.

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<![CDATA[Loss of cytoplasmic survivin expression is an independent predictor of poor prognosis in radically operated prostate cancer patients]]> https://www.researchpad.co/product?articleinfo=Nc3688025-4c13-477c-86d5-228430a0bf68

Abstract

Survivin is an inhibitor of apoptosis. Aberrant survivin expression occurs in malignant tumors and has often been linked to unfavorable patient outcome. Here we analyzed 12 432 prostate cancers by immunohistochemistry. Survivin immunostaining was regularly expressed at high levels in normal prostate epithelium but expression was often reduced in prostate cancers. Among 9492 evaluable prostate cancers, 9% expressed survivin strongly, 19% moderately, 28% weakly, and 44% lacked it. Loss of cytoplasmic survivin was seen in advanced tumor stage, higher Gleason score, preoperative PSA levels, and Ki‐67 labeling index, and associated with earlier PSA recurrence (P < .0001). Survivin loss was significantly more common in cancers carrying TMPRSS2:ERG fusions (61% survivin negative) than in ERG wild‐type cancers (32% survivin negative; P < .0001). Multivariate analysis revealed that reduced cytoplasmic survivin expression predicted poor prognosis independent from Gleason score, pT, pN, and serum PSA level. This was valid for ERG‐positive and ERG‐negative cancers. Survivin expression loss even retained its prognostic impact in 1020 PTEN deleted cancers, a group that is already characterized by dismal patient prognosis. In conclusion, reduced survivin expression is associated with more aggressive tumors and inferior prognosis in prostate cancer.

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