Background: Enhanced recovery after surgery (ERAS) pathways have been shown to considerably reduce complications, length of stay and costs after most of surgical procedures by standardised application of best evidence-based perioperative care. The aim was to elaborate dedicated recommendations for

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8527 Background: IBM Watson for Oncology is an artificial intelligence cognitive computing system that provides confidence-ranked, evidence-based treatment recommendations for cancer. In the present study, we examine the level of agreement for lung and colorectal cancer therapy between the multidisciplinary tumour board from Manipal Comprehensive Cancer Centre in Bangalore, India, and Watson for Oncology. Methods: Watson for Oncology is a Memorial Sloan Kettering Cancer Center (New York, USA) trained cognitive computing system that uses natural language processing and machine learning to provide treatment recommendations. It processes structured and unstructured data from medical literature, treatment guidelines, medical records, imaging, lab and pathology reports, and the expertise of Memorial Sloan Kettering experts to formulate therapeutic recommendations. Treatment recommendations are provided in three categories: recommended, for consideration and not recommended. In this report we provide the results of the independent and blinded evaluation by the multidisciplinary tumour board and Watson for Oncology of 362 total cancer cases comprised of 112 lung, 126 colon and 124 rectal cancers seen at the Centre within the last three years. The recommendations of the two agents were compared for agreement and considered concordant when the tumour board recommendation was included in the recommended or for consideration categories of the treatment advisor. Results: Overall, treatment recommendations were concordant in 96.4% of lung, 81.0% of colon and 92.7% of rectal cancer cases. By tumour stage, treatment recommendations were concordant in 88.9% of localized and 97.9% of metastatic lung cancer, 85.5% of localized and 76.6% of metastatic colon cancer, and 96.8% of localized and 80.6% of metastatic rectal cancer. Conclusions: Treatment recommendations made by the Manipal multidisciplinary tumour board and Watson for Oncology were highly concordant in the cancers examined. This cognitive computing technology holds much promise in helping oncologists make information intensive, evidence based treatment decisions.

BackgroundPeritoneal metastasis (PM) is a common occurrence in gynaecological and gastrointestinal cancers and is associated with poor survival. Patients typically present with ascites, abdominal pain, malnutrition, nausea, emesis, and bowel obstruction which significantly compromise the quality of life (QoL). The treatment remains a particular challenge, with palliative systemic chemotherapy being the standard of care. However, the efficacy of systemic chemotherapy is poor but with high potential for side effects and complications. QoL plays an important role in patients with PM and is deteriorating continuously until death. Thus, there is an obvious medical need for better therapeutic options in PM for prolonging survival and preserving QoL by reducing both disease-related symptoms and therapy side effects. Pressurized intraperitoneal aerosol chemotherapy (PIPAC) is a novel technique for delivering pressurized normothermic chemotherapy into the abdominal cavity as an aerosol. This concept seems to enhance the effectiveness of intraperitoneal chemotherapy by taking advantage of the physical properties of gas and pressure by generating an artificial pressure gradient and enhancing tissue uptake and distributing drugs homogeneously within the closed and expanded peritoneal cavity.MethodsThe primary objective of this study is to assess QoL and symptoms in a consecutive cohort of patients with PM treated with PIPAC procedure in comparison with conventional systemic intravenous chemotherapy. QoL is assessed prospectively using European Organization for Research and Treatment of Cancer (EORTC) QLQ-C30(Version 3.0) questionnaire. QLQ-C30 is a 30-question self-administered questionnaire inquiring about global health status, 9 individual symptoms, and 5 functional scales. Baseline QoL is measured using the global physical health functional score, and symptom scores derived from EORTC QLQ30 questionnaire before starting therapy, followed by at 60, 120, and 180 days after the first intervention. Calculated sample size is 119 and rounded to 120. For each treatment group, sample size of 60 will be enrolled; Intervention model: IV chemotherapy group (control group) and PIPAC group (experimental group); Study type: prospective randomized control intervention trialDiscussionAll consecutive patients diagnosed with advanced end-stage PM are randomized to be treated with PIPAC or IV chemotherapy. The primary objective of this study is to determine the QoL after three cycles of PIPAC in comparison with six cycles of systemic chemotherapy. The secondary outcome measures include morbidity and mortality. Analysis is by intention to treat.ResultsThe effect of systemic chemotherapy remains limited on the peritoneum due to poor vascularization and low penetration. Side effects after systemic chemotherapy for PM are relatively frequent. QoL plays an important role in these patients and is deteriorating continuously due to the disease or therapy related. Thus, there is need for better therapeutic options for prolonging survival and preserving QoL by reducing both disease-related symptoms and therapy side effects. PIPAC is a novel minimally invasive repeatable treatment modality which demonstrated potentially encouraging tumour response and only minimal toxicity in patients with PM of various origins. It can optimize local drug delivery and improve clinical outcome due to superior pharmacological properties as compared to systemic chemotherapy.Trial registrationREF/2018/08/021225 Registered on Clinical Trials Registry-India (CTRI); www.ctri.nic.in