Real-world behavioral restrictional practices of cancer patients (pts)

Researched by Belong.life and Sourasky Medical Center, Oncology Division. published by ASCO Authors: Eliya Shachar, Noy Moisa, Shira Peleg-Hasson, Tamar Safra, Ido Wolf, Daniel A. Vorobiof Background: Quality of life (QoL) assessments do not measure pts’ ability to maintain normal daily activities during cancer therapy. Misbeliefs might promote avoidance of activities perceived as dangerous, compromising pts […]

Real world data evidence on cancer patients awareness and knowledge of cancer associated thrombosis (CAT) events

Researched by Belong.life and Hematology Institute, University Hospital Assuta Samson Ashdod. published by ASCO Authors: Adrian Marcelo Duek, Bozhena Haikin, Alon Litvin, Daniel A. Vorobiof Background: Cancer pts are mostly unaware of the higher than normal risk of developing a CAT event. A recently reported European survey, with 745 participants, showed that just above two-thirds (69%) […]

Covid 19 infection leading to a subsequent new primary cancer diagnosis, Real-world data (RWD) analysis on members of Belong.life, a global cancer application

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Researched by Belong.Life and published by ASCO Authors: Daniel A. Vorobiof, Bozhena Haikin, Alon Litvin, Irad Deutsch, Eliran Malki. Background: Some known viral infections can lead to a diagnosis of cancer (e.g: HPV, HIV, EBV, etc.) Anecdotical reports of a Covid 19 infection, and the subsequent diagnosis of a new cancer have been mentioned by […]

Identifying The Patient Journey And Treatment Lines Patterns In Metastatic Pancreatic Cancer​

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Researched by Belong.Life and published by ASCO, 2018 Authors: Daniel Vorobiof, Irad Deutsch, Eliran Malki, Maytal Bivas-Benita Introduction: Checkpoint inhibitors such as programmed cell death receptor 1 (PD-1) antibodies have significantly improved the prognosis in several malignancies. While treatment with the PD-1 targeting antibodies, pembrolizumab and nivolumab, has substantial clinical benefit, it is associated with […]

Mapping PD-1 Inhibitors’ Side Effects Using Patient Reported Outcomes

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Researched by Belong.Life and published by ASCOData from the Belong PPN successfully captured the spectrum of PD-1 inhibitors’ reported AEs. Analyzing PRO of post approval treatments could provide deeper understanding of treatment patterns, expose limiting AE that bear implications on cost of treatment, indicate patients’ quality of life (QOL), improve management recommendations and provide a […]

Unveiling The Real-World Outcomes Of Breast Cancer Patients With Taxanes-Induced Neuropathy Using A Digital Patient-Powered Network

ASCO 2019 ANNUAL MEETING

Researched by Belong.Life and published by ASCO, 2019 Authors: Raanan Berger, Lior Hasid, Irad Deutsch, Eliran Malki, Maytal Bivas-Benita Background: Taxanes-induced neuropathy is common in BC patients receiving taxanes, forcing dose reductions and treatment delays and posing serious challenges for the long-term patient QoL. Discovering neuropathy predictors in patients could guide better treatment decisions, improved […]

Creating The Real-World Medical Record: Using Digital Patient-Generated Data To Create An Updated Picture Of Patients Outcomes

ASCO 2019 ANNUAL MEETING

Researched by Belong.Life and published by ASCO, 2019 Authors: Maytal Bivas-Benita , Irad Deutsch, Eliran Malki, Lior Hasid Background: Value-based healthcare requires integration of real-world data (RWD) generated by patients in parallel to clinical documentation. This gives a holistic perspective of the patients’ health and care and could lead to reduced costs and better patient […]

Patients Reported Outcomes In Breast Cancer: Physical, Emotional Side Effects, Financial Toxicity, And Complementary Usage Relations

ASCO 2019 ANNUAL MEETING

Researched by Belong.Life and published by ASCO, 2019 Authors: Daniel A. Vorobiof, Eliran Malki, Irad Deutsch, Lior Hasid Background: RWD denotes data accumulated via electronic health records as well as cutting edge technology paired with consumer mobile devices. Artificial intelligence (AI) incorporates the use of algorithms and machine learning (ML) software to analyze complex medical […]

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