Abstract
BackgroundNext-generation sequencing provides comprehensive information about individuals’ genetic makeup and is commonplace in oncology clinical practice. However, the utility of genetic information in the clinical decision-making process has not been examined extensively from a real-world, data-driven perspective. Through mining real-world data (RWD) from clinical notes, we could extract patients’ genetic information and further associate treatment decisions with genetic information.MethodsWe proposed a real-world evidence (RWE) study framework that incorporates context-based natural language processing (NLP) methods and data quality examination before final association analysis. The framework was demonstrated in a Foundation-tested women cancer cohort (N = 196). Upon retrieval of patients’ genetic information using NLP system, we assessed the completeness of genetic data captured in unstructured clinical notes according to a genetic data-model. We examined the distribution of different topics regarding BRCA1/2 throughout patients’ treatment process, and then analyzed the association between BRCA1/2 mutation status and the discussion/prescription of targeted therapy.ResultsWe identified seven topics in the clinical context of genetic mentions including: Information, Evaluation, Insurance, Order, Negative, Positive, and Variants of unknown significance. Our rule-based system achieved a precision of 0.87, recall of 0.93 and F-measure of 0.91. Our machine learning system achieved a precision of 0.901, recall of 0.899 and F-measure of 0.9 for four-topic classification and a precision of 0.833, recall of 0.823 and F-measure of 0.82 for seven-topic classification. We found in result-containing sentences, the capture of BRCA1/2 mutation information was 75%, but detailed variant information (e.g. variant types) is largely missing. Using cleaned RWD, significant associations were found between BRCA1/2 positive mutation and targeted therapies.ConclusionsIn conclusion, we demonstrated a framework to generate RWE using RWD from different clinical sources. Rule-based NLP system achieved the best performance for resolving contextual variability when extracting RWD from unstructured clinical notes. Data quality issues such as incompleteness and discrepancies exist thus manual data cleaning is needed before further analysis can be performed. Finally, we were able to use cleaned RWD to evaluate the real-world utility of genetic information to initiate a prescription of targeted therapy.
Highlights
Next-generation sequencing provides comprehensive information about individuals’ genetic makeup and is commonplace in oncology clinical practice
We were able to use cleaned realworld data (RWD) to evaluate the real-world utility of genetic information to initiate a prescription of targeted therapy
We were able to use cleaned RWD to conduct a real-word evidence study regarding the association between BRCA1/2 mutation and prescription of Poly-adenosyldiphosphate-ribose polymerase (PARP) inhibitors (“Association analysis between mutation and targeted therapy” section)
Summary
Next-generation sequencing provides comprehensive information about individuals’ genetic makeup and is commonplace in oncology clinical practice. BRCA1/2 germline mutations are considered a risk factor for breast, ovarian, and other hereditary cancers [1, 2]. Poly-adenosyldiphosphate-ribose polymerase (PARP) inhibitors are a relatively new type of cancer treatment initially designed to target HRR defects, especially for people with inherited mutations in BRCA1/2 [4]. Recent studies prove that mechanisms and treatment susceptibility of BRCA-mutant tumors are not restricted to inherited tumor – both familial and sporadic tumor share common clinical features [5]: extreme levels of genomic instability, basal-like transcriptomic signature (genes expression profile similar to normal breast myoepithelial layer), and triple-negative phenotype (oestrogen receptor, progesterone receptor and ERBB2 oncogene not expressed or amplified). The new understanding of BRCAness has driven wider adoption of Precision Medicine approaches, PAPR inhibitor to treat sporadic BRCA-mutant cancer With refined knowledge of the biological mechanism of BRCA1/2 tumor suppressor functions over the past decade, the concept of “BRCAness” was introduced as: “A phenocopy of BRCA1 or BRCA2 mutation; it describes the situation in which an HRR defect exists in a tumor in the absence of a germline BRCA1 or BRCA2 mutation.” The new understanding of BRCAness has driven wider adoption of Precision Medicine approaches, PAPR inhibitor to treat sporadic BRCA-mutant cancer
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