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Concordance Study Between IBM Watson for Oncology and Clinical Practice for Patients with Cancer in China.

ABSTRACT: BACKGROUND:IBM Watson for Oncology (WFO), which can use natural language processing to evaluate data in structured and unstructured formats, has begun to be used in China. It provides physicians with evidence-based treatment options and ranks them in three categories for treatment decision support. This study was designed to examine the concordance between the treatment recommendation proposed by WFO and actual clinical decisions by oncologists in our cancer center, which would reflect the differences of cancer treatment between China and the U.S. PATIENTS AND METHODS:Retrospective data from 362 patients with cancer were ingested into WFO from April 2017 to October 2017. WFO recommendations were provided in three categories: recommended, for consideration, and not recommended. Concordance was analyzed by comparing the treatment decisions proposed by WFO with those of the multidisciplinary tumor board. Concordance was achieved when the oncologists' treatment decisions were in the recommended or for consideration categories in WFO. RESULTS:Ovarian cancer showed the highest concordance, which was 96%. Lung cancer and breast cancer obtained a concordance of slightly above 80%. The concordance of rectal cancer was 74%, whereas colon cancer and cervical cancer showed the same concordance of 64%. In particular, the concordance of gastric cancer was very low, only 12%, and 88% of cases were under physicians choice. CONCLUSION:Different cancer types showed different concordances, and only gastric cancers were significantly less likely to be concordant. Incidence and pharmaceuticals may be the major cause of discordance. To be comprehensively and rapidly applied in China, WFO needs to accelerate localization. ClinicalTrials.gov Identifier: NCT03400514. IMPLICATIONS FOR PRACTICE:IBM Watson for Oncology (WFO) has begun to be used in China. In this study, concordance was examined between the treatment recommendation proposed by WFO and clinical decisions for 362 patients in our cancer center, which could reflect the differences of cancer treatment between China and the U.S. Different cancer types showed different concordances, and only gastric cancers were significantly less likely to be concordant. Incidence and pharmaceuticals may be the major causes of discordance. To be comprehensively and rapidly applied in China, WFO needs to accelerate localization. This study may have a significant effect on application of artificial intelligence systems in China.

SUBMITTER: Zhou N

PROVIDER: S-EPMC6656482 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Concordance Study Between IBM Watson for Oncology and Clinical Practice for Patients with Cancer in China.

Zhou Na N Zhang Chuan-Tao CT Lv Hong-Ying HY Hao Chen-Xing CX Li Tian-Jun TJ Zhu Jing-Juan JJ Zhu Hua H Jiang Man M Liu Ke-Wei KW Hou He-Lei HL Liu Dong D Li Ai-Qin AQ Zhang Guo-Qing GQ Tian Zi-Bin ZB Zhang Xiao-Chun XC

The oncologist 20180904 6

<h4>Background</h4>IBM Watson for Oncology (WFO), which can use natural language processing to evaluate data in structured and unstructured formats, has begun to be used in China. It provides physicians with evidence-based treatment options and ranks them in three categories for treatment decision support. This study was designed to examine the concordance between the treatment recommendation proposed by WFO and actual clinical decisions by oncologists in our cancer center, which would reflect t ...[more]

PMID: 30181315

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Project description:BACKGROUND:With the increasing number of cancer treatments, the emergence of multidisciplinary teams (MDTs) provides patients with personalized treatment options. In recent years, artificial intelligence (AI) has developed rapidly in the medical field. There has been a gradual tendency to replace traditional diagnosis and treatment with AI. IBM Watson for Oncology (WFO) has been proven to be useful for decision-making in breast cancer and lung cancer, but to date, research on gastric cancer is limited. OBJECTIVE:This study compared the concordance of WFO with MDT and investigated the impact on patient prognosis. METHODS:This study retrospectively analyzed eligible patients (N=235) with gastric cancer who were evaluated by an MDT, received corresponding recommended treatment, and underwent follow-up. Thereafter, physicians inputted the information of all patients into WFO manually, and the results were compared with the treatment programs recommended by the MDT. If the MDT treatment program was classified as "recommended" or "considered" by WFO, we considered the results concordant. All patients were divided into a concordant group and a nonconcordant group according to whether the WFO and MDT treatment programs were concordant. The prognoses of the two groups were analyzed. RESULTS:The overall concordance of WFO and the MDT was 54.5% (128/235) in this study. The subgroup analysis found that concordance was less likely in patients with human epidermal growth factor receptor 2 (HER2)-positive tumors than in patients with HER2-negative tumors (P=.02). Age, Eastern Cooperative Oncology Group performance status, differentiation type, and clinical stage were not found to affect concordance. Among all patients, the survival time was significantly better in concordant patients than in nonconcordant patients (P<.001). Multivariate analysis revealed that concordance was an independent prognostic factor of overall survival in patients with gastric cancer (hazard ratio 0.312 [95% CI 0.187-0.521]). CONCLUSIONS:The treatment recommendations made by WFO and the MDT were mostly concordant in gastric cancer patients. If the WFO options are updated to include local treatment programs, the concordance will greatly improve. The HER2 status of patients with gastric cancer had a strong effect on the likelihood of concordance. Generally, survival was better in concordant patients than in nonconcordant patients.

Project description:BackgroundPharmacodynamic biomarkers are becoming increasingly valuable for assessing drug activity and target modulation in clinical trials. However, identifying quality biomarkers is challenging due to the increasing volume and heterogeneity of relevant data describing the biological networks that underlie disease mechanisms. A biological pathway network typically includes entities (e.g. genes, proteins and chemicals/drugs) as well as the relationships between these and is typically curated or mined from structured databases and textual co-occurrence data. We propose a hybrid Natural Language Processing and directed relationships-based network analysis approach using IBM Watson for Drug Discovery to rank all human genes and identify potential candidate biomarkers, requiring only an initial determination of a specific target-disease relationship.MethodsThrough natural language processing of scientific literature, Watson for Drug Discovery creates a network of semantic relationships between biological concepts such as genes, drugs, and diseases. Using Bruton's tyrosine kinase as a case study, Watson for Drug Discovery's automatically extracted relationship network was compared with a prominent manually curated physical interaction network. Additionally, potential biomarkers for Bruton's tyrosine kinase inhibition were predicted using a matrix factorization approach and subsequently compared with expert-generated biomarkers.ResultsWatson's natural language processing generated a relationship network matching 55 (86%) genes upstream of BTK and 98 (95%) genes downstream of Bruton's tyrosine kinase in a prominent manually curated physical interaction network. Matrix factorization analysis predicted 11 of 13 genes identified by Merck subject matter experts in the top 20% of Watson for Drug Discovery's 13,595 ranked genes, with 7 in the top 5%.ConclusionTaken together, these results suggest that Watson for Drug Discovery's automatic relationship network identifies the majority of upstream and downstream genes in biological pathway networks and can be used to help with the identification and prioritization of pharmacodynamic biomarker evaluation, accelerating the early phases of disease hypothesis generation.

Project description:PurposeTo provide evidence-based recommendations to oncologists and others for the treatment of patients with metastatic pancreatic cancer.MethodsAmerican Society of Clinical Oncology convened an Expert Panel of medical oncology, radiation oncology, surgical oncology, gastroenterology, palliative care, and advocacy experts to conduct a systematic review of the literature from April 2004 to June 2015. Outcomes were overall survival, disease-free survival, progression-free survival, and adverse events.ResultsTwenty-four randomized controlled trials met the systematic review criteria.RecommendationsA multiphase computed tomography scan of the chest, abdomen, and pelvis should be performed. Baseline performance status and comorbidity profile should be evaluated. Goals of care, patient preferences, treatment response, psychological status, support systems, and symptom burden should guide decisions for treatments. A palliative care referral should occur at first visit. FOLFIRINOX (leucovorin, fluorouracil, irinotecan, and oxaliplatin; favorable comorbidity profile) or gemcitabine plus nanoparticle albumin-bound (NAB) -paclitaxel (adequate comorbidity profile) should be offered to patients with Eastern Cooperative Oncology Group performance status (ECOG PS) 0 to 1 based on patient preference and support system available. Gemcitabine alone is recommended for patients with ECOG PS 2 or with a comorbidity profile that precludes other regimens; the addition of capecitabine or erlotinib may be offered. Patients with an ECOG PS ≥ 3 and poorly controlled comorbid conditions should be offered cancer-directed therapy only on a case-by-case basis; supportive care should be emphasized. For second-line therapy, gemcitabine plus NAB-paclitaxel should be offered to patients with first-line treatment with FOLFIRINOX, an ECOG PS 0 to 1, and a favorable comorbidity profile; fluorouracil plus oxaliplatin, irinotecan, or nanoliposomal irinotecan should be offered to patients with first-line treatment with gemcitabine plus NAB-paclitaxel, ECOG PS 0 to 1, and favorable comorbidity profile, and gemcitabine or fluorouracil should be offered to patients with either an ECOG PS 2 or a comorbidity profile that precludes other regimens. Additional information is available at www.asco.org/guidelines/MetPC and www.asco.org/guidelineswiki.

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Concordance Study Between IBM Watson for Oncology and Clinical Practice for Patients with Cancer in China.

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Concordance Study Between IBM Watson for Oncology and Clinical Practice for Patients with Cancer in China.

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