Watson for oncology decision system for treatment consistency study in breast cancer

Liu, Yaobang; Huo, Xingfa; Li, Qi; Li, Yishuang; Shen, Guoshuang; Wang, Miaozhou; Ren, Dengfeng; Zhao, Fuhua; Liu, Zhen; Zhao, Jiuda; Liu, Xinlan

doi:10.1007/s10238-022-00896-z

Cited by 7 publications

(5 citation statements)

References 23 publications

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“…Thirteen studies of breast cancer were conducted, involving a total of 7786 subjects ( 15 , 16 , 18 – 21 , 27 , 34 , 36 , 38 , 43 – 45 ). The number of participants per study varied widely, ranging from 55 ( 27 ) to 1,977 ( 36 ).…”

Section: Resultsmentioning

confidence: 99%

Use and accuracy of decision support systems using artificial intelligence for tumor diseases: a systematic review and meta-analysis

Oehring,

Ramasetti,

et al. 2023

Front. Oncol.

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BackgroundFor therapy planning in cancer patients multidisciplinary team meetings (MDM) are mandatory. Due to the high number of cases being discussed and significant workload of clinicians, Clinical Decision Support System (CDSS) may improve the clinical workflow.MethodsThis review and meta-analysis aims to provide an overview of the systems utilized and evaluate the correlation between a CDSS and MDM.ResultsA total of 31 studies were identified for final analysis. Analysis of different cancers shows a concordance rate (CR) of 72.7% for stage I-II and 73.4% for III-IV. For breast carcinoma, CR for stage I-II was 72.8% and for III-IV 84.1%, P≤ 0.00001. CR for colorectal carcinoma is 63% for stage I-II and 67% for III-IV, for gastric carcinoma 55% and 45%, and for lung carcinoma 85% and 83% respectively, all P>0.05. Analysis of SCLC and NSCLC yields a CR of 94,3% and 82,7%, P=0.004 and for adenocarcinoma and squamous cell carcinoma in lung cancer a CR of 90% and 86%, P=0.02.ConclusionCDSS has already been implemented in clinical practice, and while the findings suggest that its use is feasible for some cancers, further research is needed to fully evaluate its effectiveness.

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Section: Resultsmentioning

confidence: 99%

Use and accuracy of decision support systems using artificial intelligence for tumor diseases: a systematic review and meta-analysis

Oehring,

Ramasetti,

et al. 2023

Front. Oncol.

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“…Comparative studies between breast cancer characteristics in China and the United States reveal that China experiences a higher prevalence of advanced tumors and a lower estrogen receptor positivity rate. 12 In addition, China has witnessed a steady annual rise in breast cancer incidence. Data reflecting China’s cancer burden underscores an ascending trend in breast cancer incidence and mortality among Chinese women from 2000 to 2015.…”

Section: Discussionmentioning

confidence: 99%

“…WFO, an AI-powered tumor treatment decision system, delivers recommendations aligned with MDT perspectives based on patient data. 12 Yet, its effective implementation in China necessitates localization and clinical research evaluation, considering factors like regional differences in guidelines and medication access. Presently, WFO’s availability in mainland China is limited due to its collaboration with MD Anderson Center.…”

Section: Introductionmentioning

confidence: 99%

Consistency of CSCO AI with Multidisciplinary Clinical Decision-Making Teams in Breast Cancer: A Retrospective Study

Xu,

Wang,

Yang

et al. 2024

BCTT

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Background The Chinese Society of Clinical Oncology Artificial Intelligence System (CSCO AI) serves as a clinical decision support system developed utilizing Chinese breast cancer data. Our study delved into the congruence between breast cancer treatment recommendations provided by CSCO AI and their practical application in clinical settings. Methods A retrospective analysis encompassed 537 breast cancer patients treated at the Second Affiliated Hospital of Anhui Medical University between January 2017 and December 2022. Proficient senior oncology researchers manually input patient data into the CSCO AI system. “Consistent” and “Inconsistent” treatment categories were defined by aligning our treatment protocols with the classification system in the CSCO AI recommendations. Cases that initially showed inconsistency underwent a second evaluation by the Multi-Disciplinary Treatment (MDT) team at the hospital. Concordance was achieved when MDTs’ treatment suggestions were in the ‘Consistent’ categories. Results An impressive 80.4% concurrence was observed between actual treatment protocols and CSCO AI recommendations across all breast cancer patients. Notably, the alignment was markedly higher for stage I (85.02%) and stage III (88.46%) patients in contrast to stage II patients (76.06%, P=0.023). Moreover, there was a significant concordance between invasive ductal carcinoma and lobular carcinoma (88.46%). Interestingly, triple-negative breast cancer (TNBC) exhibited a high concordance rate (87.50%) compared to other molecular subtypes. When contrasting MDT-recommended treatments with CSCO AI decisions, an overall 92.4% agreement was established. Furthermore, a logistic multivariate analysis highlighted the statistical significance of age, menstrual status, tumor type, molecular subtype, tumor size, and TNM stage in influencing consistency. Conclusion In the realm of breast cancer treatment, the alignment between recommendations offered by CSCO AI and those from MDT is predominant. CSCO AI can be a useful tool for breast cancer treatment decisions.

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“…[27,28] In these cases, blood vessels in extremity or abdomen, such as femoral artery, brachial artery, and abdominal aorta are highly vulnerable. [29] Quick and efficient completion of multiple vascular anastomoses for these emergency situations can be life-saving outcomes (for ≈0.7 mm diameter, coagulopathic blood, 27 min time saving per anastomosis was saved). Also, diameter of the carotid artery used in this study was 0.64 mm which belongs to small diameter ranges considering human blood vessels, indicating that the use of adhesive, selfwrapping films is suitable for small diameter vessel anastomosis.…”

Section: Discussion For Less-suture Anastomosismentioning

confidence: 99%

Less‐Suture Vascular Anastomosis: Development of Alternative Protocols with Multifunctional Self‐Wrapping, Transparent, Adhesive, and Elastic Biomaterials

Lee

Jung³

et al. 2023

Advanced Materials

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Blood vessel anastomosis by suture is a life‐saving, yet time‐consuming and labor‐intensive operation. While suture‐less alternatives utilizing clips or related devices are developed to address these shortcomings, suture anastomosis is still overwhelmingly used in most cases. In this study, practical “less‐suture” strategies are proposed, rather than ideal “suture‐less” methods, to reflect real‐world clinical situations. In the case of rat artery (d = 0.64 mm) anastomosis, the less‐suture anastomosis involves the application of thin, adhesive, transparent, and self‐wrapping films to the site. This surprisingly reduces the number of stitches required from ten (without films) to four (with films), saving 27 min of operating time per vessel. Furthermore, the decreased number of stitches largely alleviates fibrosis‐mediated wall‐thickening. Thus, a less‐suture strategy is particularly useful for anastomosis of multiple vessels in emergency conditions and small‐diameter vessels.

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Watson for oncology decision system for treatment consistency study in breast cancer

Cited by 7 publications

References 23 publications

Use and accuracy of decision support systems using artificial intelligence for tumor diseases: a systematic review and meta-analysis

Use and accuracy of decision support systems using artificial intelligence for tumor diseases: a systematic review and meta-analysis

Consistency of CSCO AI with Multidisciplinary Clinical Decision-Making Teams in Breast Cancer: A Retrospective Study

Less‐Suture Vascular Anastomosis: Development of Alternative Protocols with Multifunctional Self‐Wrapping, Transparent, Adhesive, and Elastic Biomaterials

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