Using an Adapted Tumor Board Evaluation Tool for Quality Assessment of a Thoracic Multidisciplinary Cancer Conference: A Pilot Study.

PURPOSE: Multidisciplinary cancer conferences (MCCs) are crucial for the management of complex oncology patients. Tools to evaluate MCC performance are needed. The aim of this pilot study was to assess the applicability of an existing validated performance assessment tool to evaluate the quality of thoracic MCCs (T-MCCs). METHODS: Data were collected from weekly T-MCCs over a 5-week period using the MCC Performance Assessment Tool and a self-assessment survey. Audio recordings were used to supplement observation notes. Case presentation, discussion duration, decision making contribution, recommendations, and consensus were captured. Quality of information and contribution were rated on a 1-5 scale. The data were analyzed using descriptive statistics to calculate means and composite scores representing overall MCC performance. RESULTS: A total of 44 cases were observed at the T-MCC with the mean presentation and discussion time of 6 minutes and 22 seconds. Quality of case history, radiologic and pathological information, and reason for case discussion were rated above average (>3), whereas inclusion of comorbidities and patient views were rated below average. Surgical oncologists had a higher discussion contribution compared with medical and radiation oncologists (3.6 v 2.9 and 2.4, respectively). The overall mean composite score was 55.9 (deemed average) with no cases categorized as poor or excellent. Radiologists and pathologists had mean preparation times of 81.7 and 144.0 minutes, respectively. CONCLUSION: This study demonstrated the applicability of a previously validated tool to assess the quality of a T-MCC at an academic comprehensive cancer center. The tool was found to be useful in identifying elements of the T-MCC process that needed improvement.

Impact of a Thoracic Multidisciplinary Conference on Lung Cancer Outcomes.

BACKGROUND: With the complexity of cancer treatment rising, the role of multidisciplinary conferences (MDCs) in making diagnostic and treatment decisions has become critical. This study evaluated the impact of a thoracic MDC (T-MDC) on lung cancer care quality and survival. METHODS: Lung cancer cases over 7 years were identified from the Roswell Park cancer registry system. The survival rates and treatment plans of 300 patients presented at the MDC were compared with 300 matched patients. The National Comprehensive Cancer Network (NCCN) guidelines were used to define the standard of care. The compliance of care plans with NCCN guidelines was summarized using counts and percentages, with comparisons made using the Fisher exact test. Survival outcomes were summarized using Kaplan-Meier methods. RESULTS: There was improvement in median overall survival (36.9 vs 19.3 months; P < .001) and cancer-specific survival (48 vs 28.1 months; P < .001) for lung cancer patients discussed at the T-MDC compared with controls. These differences were statistically significant in patients with stages III/IV disease but not in patients with stages I/II disease. The NCCN guidelines compliance rate of treatment plans improved from 80% to 94% (P < .001) after MDC discussion. MDC recommendations resulted in treatment plan changes in 123 of 300 patients (41%). CONCLUSIONS: Our results suggest that lung cancer patients have a survival benefit from MDC discussion compared with controls. Patients with advanced disease (stages III and IV) benefited the most. Further research is necessary to understand the precise mechanisms that drive these results.

Building a specialized lexicon for breast cancer clinical trial subject eligibility analysis.

A natural language processing (NLP) application requires sophisticated lexical resources to support its processing goals. Different solutions, such as dictionary lookup and MetaMap, have been proposed in the healthcare informatics literature to identify disease terms with more than one word (multi-gram disease named entities). Although a lot of work has been done in the identification of protein- and gene-named entities in the biomedical field, not much research has been done on the recognition and resolution of terminologies in the clinical trial subject eligibility analysis. In this study, we develop a specialized lexicon for improving NLP and text mining analysis in the breast cancer domain, and evaluate it by comparing it with the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT). We use a hybrid methodology, which combines the knowledge of domain experts, terms from multiple online dictionaries, and the mining of text from sample clinical trials. Use of our methodology introduces 4243 unique lexicon items, which increase bigram entity match by 38.6% and trigram entity match by 41%. Our lexicon, which adds a significant number of new terms, is very useful for matching patients to clinical trials automatically based on eligibility matching. Beyond clinical trial matching, the specialized lexicon developed in this study could serve as a foundation for future healthcare text mining applications.

The clinical significance of metastatic breast carcinoma to intramammary lymph node.

The incidence of involved intramammary lymph node (intra-MLN) with breast carcinoma (BC) is rare. Its clinical significance and impact on the clinical decision making is unclear. A total of 113 BC cases with at least one positive intra-MLN were collected from 11 academic institutions. The inclusion criteria were subsequent axillary lymph node dissection, and the availability of information on T-stage, size of node metastasis, extranodal extension status, biomarkers status, and clinical follow-up. Stage 4 cases and/or neo-adjuvant treated patients were excluded. AJCC TN-stage was calculated twice, with and without intra-MLN. Five-year overall survival (OS) and relapse (local and/or distant)-free survival (RFS) were calculated and correlated with the clinicopathologic variables. Excluding intra-MLN, TN-stage correlated with OS (P = .016) but not with RFS (P = .19). However, when intra-MLN was included, TN-stage correlated with both OS (P < .001) and RFS (P = .016). In the multivariate analysis, when intra-MLN was excluded, only radiation therapy (RT) correlated with RFS (HR = 0.19, 95% CI: 0.054-0.66, P = .009). However, when intra-MLN was included in the TN-stage both RT (HR = 0.13, 95% CI: 0.04-0.45, P = .001) and TN-stage 3 (HR = 8.92, 95% CI: 1.47-54, P = .017) correlated with RFS. Tumor multifocality was the only variable correlated with OS when the intra-MLN involvement was excluded. When intra-MLN was included, multifocality became insignificant but TN-stage 3 correlated with OS (HR = 8.59, 95% CI: 1.06-69.71, P = .044). Positive intra-MLN is an independent factor in predicting both RFS and OS.

Clinical Tractor: A Framework for Automatic Natural Language Understanding of Clinical Practice Guidelines.

Computational representations of the semantic knowledge embedded within clinical practice guidelines (CPGs) may be a significant aid in creating computer interpretable guidelines (CIGs). Formalizing plain text CPGs into CIGs manually is a laborious and burdensome task, even using CIG tools and languages designed to improve the process. Natural language understanding (NLU) systems perform automated reading comprehension, parsing text and using reasoning to convert syntactic information from unstructured text into semantic information. Influenced by successful systems used in other domains, we present the architecture for a system which uses NLU approaches to create semantic representations of entire CPGs. In the future, these representations may be used to generate CIGs.

Factors influencing malignant mesothelioma survival: a retrospective review of the National Mesothelioma Virtual Bank cohort.

Background: Malignant mesothelioma (MM) is a rare but deadly malignancy with about 3,000 new cases being diagnosed each year in the US.  Very few studies have been performed to analyze factors associated with mesothelioma survival, especially for peritoneal presentation. The overarching aim of this study is to examine survival of the cohort of patients with malignant mesothelioma enrolled in the National Mesothelioma Virtual Bank (NMVB).   Methods:  888 cases of pleural and peritoneal mesothelioma cases were selected from the NMVB database, which houses data and associated biospecimens for over 1400 cases that were diagnosed from 1990 to 2017. Kaplan Meier's method was performed for survival analysis. The association between prognostic factors and survival was estimated using Cox Hazard Regression method and using R software for analysis. Results: The median overall survival (OS) rate of all MM patients, including pleural and peritoneal mesothelioma cases is 15 months (14 months for pleural and 31 months for peritoneal).  Significant prognostic factors associated with improved survival of malignant mesothelioma cases in this NMVB cohort were younger than 45, female gender, epithelioid histological subtype, stage I, peritoneal occurrence, and having combination treatment of surgical therapy with chemotherapy. Combined surgical and chemotherapy treatment was associated with improved survival of 23 months in comparison to single line therapies. Conclusions: There has not been improvement in the overall survival for patients with malignant mesothelioma over many years with current available treatment options. Our findings show that combined surgical and chemotherapy treatment in peritoneal mesothelioma is associated with improved survival compared to local therapy alone.

The role of skin ulceration in breast carcinoma staging and outcome.

Breast carcinoma with skin ulceration (SU) is considered a locally advanced disease. The purpose of the study is to investigate if SU is an independent adverse factor. Breast carcinoma patients with SU (n=111) were included in the study. A subset (n=38, study cohort) was matched with cases that had no SU (n=38, matched cohort); the survival analyses were compared between these groups. Then, cases (n=80) were staged independent from SU into stage I, II or III. Disease free survival (DFS) and overall survival (OS) were analyzed. Patients with larger tumors tended to present with distant metastases more often than patients with smaller tumors (P=.004). In the matched cases, the 5-year DFS probability was 53% for the study cohort and 58% for the matched cohort; and for OS 75% for the study cohort and 84% for the matched cohort with no statistical significant difference. However, there was a trend towards worse DFS for the patients whose tumors had SU. When the cases were staged based on tumor size and node status (I, II or III), the OS was statistically significant (P=.047) but not the DFS (P=.195). Relatively small tumors with SU had an extent of disease similar to that observed in patients with early stages disease. The survival analysis suggests that SU may not be an adverse factor. However, more cases are needed to further examine this finding.

Considerations of Human Factors in the Design and Implementation of Clinical Decision Support Systems for Tumor Boards.

Critical decisions are made at tumor boards (TB). Further research is needed to guide the design and implementation of clinical decision support systems (CDSS) for highly interactive, fast-paced, and complex TB decision making. We highlight two key human factors that should be considered in the design and Implementation of CDSS for multidisciplinary deliberations: cognitive burden and trust.

A Federated Network for Translational Cancer Research Using Clinical Data and Biospecimens.

Advances in cancer research and personalized medicine will require significant new bridging infrastructures, including more robust biorepositories that link human tissue to clinical phenotypes and outcomes. In order to meet that challenge, four cancer centers formed the Text Information Extraction System (TIES) Cancer Research Network, a federated network that facilitates data and biospecimen sharing among member institutions. Member sites can access pathology data that are de-identified and processed with the TIES natural language processing system, which creates a repository of rich phenotype data linked to clinical biospecimens. TIES incorporates multiple security and privacy best practices that, combined with legal agreements, network policies, and procedures, enable regulatory compliance. The TIES Cancer Research Network now provides integrated access to investigators at all member institutions, where multiple investigator-driven pilot projects are underway. Examples of federated search across the network illustrate the potential impact on translational research, particularly for studies involving rare cancers, rare phenotypes, and specific biologic behaviors. The network satisfies several key desiderata including local control of data and credentialing, inclusion of rich phenotype information, and applicability to diverse research objectives. The TIES Cancer Research Network presents a model for a national data and biospecimen network.

Mapping nursing concepts to ontologies for evidence-based nursing.

In this paper we describe a project to map natural language expressions of nursing-related concepts to standard ontologies in support of an evidence-based nursing initiative. Natural language concept expressions are identified from syntheses of nursing knowledge and mapped to ICNP and SNOMED-CT.