Literature DB >> 30236854

Robotic-assisted vs. open radical prostatectomy: A machine learning framework for intelligent analysis of patient-reported outcomes from online cancer support groups.

Weranja Ranasinghe1, Daswin de Silva2, Tharindu Bandaragoda2, Achini Adikari2, Damminda Alahakoon2, Raj Persad3, Nathan Lawrentschuk4, Damien Bolton4.   

Abstract

BACKGROUND: The advantages of Robot-assisted laparoscopic prostatectomy (RARP) over open radical prostatectomy (ORP) in Prostate cancer perioperatively are well-established, but quality of life is more contentious. Increasingly, patients are utilising online cancer support groups (OCSG) to express themselves. Currently there is no method of analysis of these sophisticated data sources. We have used the PRIME-2 (Patient Reported Information Multidimensional Exploration version 2) framework for automated identification and intelligent analysis of decision-making, functional and emotional outcomes in men undergoing ORP vs. RARP from OCSG discussions.
METHODS: The PRIME-2 framework was developed to retrospectively analyse individualised patient-reported information from 5,157 patients undergoing RARP and 579 ORP. The decision factors, side effects, and emotions in 2 groups were analysed and compared using Chi-squared, t tests, and Pearson correlation.
RESULTS: There were no differences in Gleason score, Prostate Specific Antigen (PSA), and age between the groups. Surgeon experience and preservation of erectile function (P < 0.01) were important factors in the decision making process. There were no significant differences in urinary, sexual, or bowel symptoms between ORP and RARP on a monthly basis during the initial 12 months. Emotions expressed by patients undergoing RARP were more consistent and positive while ORP expressed more negative emotions at the time of surgery and 3 months postsurgery (P < 0.05), due to pain and discomfort, and during ninth month due to fear and anxiety of pending PSA tests.
CONCLUSIONS: ORP and RARP demonstrated similar side effect profiles for 12 months, but PRIME-2 enables identification of important quality of life features and emotions over time. It is timely for clinicians to accept OCSG as an adjunct to Prostate cancer care.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Emotions; Intelligent analysis; Machine learning; Outcomes; Robotic prostatectomy

Mesh:

Year:  2018        PMID: 30236854     DOI: 10.1016/j.urolonc.2018.08.012

Source DB:  PubMed          Journal:  Urol Oncol        ISSN: 1078-1439            Impact factor:   3.498


  4 in total

1.  Myth busting patient's pain: comparing robotic-assisted verses open radical prostatectomies.

Authors:  Benjamin Condon; Dominic Bagguley; Nathan Lawrentschuk
Journal:  Gland Surg       Date:  2020-04

2.  A Mental Health Chatbot with Cognitive Skills for Personalised Behavioural Activation and Remote Health Monitoring.

Authors:  Prabod Rathnayaka; Nishan Mills; Donna Burnett; Daswin De Silva; Damminda Alahakoon; Richard Gray
Journal:  Sensors (Basel)       Date:  2022-05-11       Impact factor: 3.847

3.  Machine learning to support social media empowered patients in cancer care and cancer treatment decisions.

Authors:  Daswin De Silva; Weranja Ranasinghe; Tharindu Bandaragoda; Achini Adikari; Nishan Mills; Lahiru Iddamalgoda; Damminda Alahakoon; Nathan Lawrentschuk; Raj Persad; Evgeny Osipov; Richard Gray; Damien Bolton
Journal:  PLoS One       Date:  2018-10-18       Impact factor: 3.240

4.  Can online support groups address psychological morbidity of cancer patients? An artificial intelligence based investigation of prostate cancer trajectories.

Authors:  Achini Adikari; Daswin de Silva; Weranja K B Ranasinghe; Tharindu Bandaragoda; Oshadi Alahakoon; Raj Persad; Nathan Lawrentschuk; Damminda Alahakoon; Damien Bolton
Journal:  PLoS One       Date:  2020-03-04       Impact factor: 3.240

  4 in total

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