Data-science-based subgroup analysis of persistent pain during 3 years after breast cancer surgery: A prospective cohort study. Issue 3 (March 2020)
- Record Type:
- Journal Article
- Title:
- Data-science-based subgroup analysis of persistent pain during 3 years after breast cancer surgery: A prospective cohort study. Issue 3 (March 2020)
- Main Title:
- Data-science-based subgroup analysis of persistent pain during 3 years after breast cancer surgery
- Authors:
- Lötsch, Jörn
Ultsch, Alfred
Kalso, Eija - Abstract:
- Abstract : BACKGROUND: Persistent pain extending beyond 6 months after breast cancer surgery when adjuvant therapies have ended is a recognised phenomenon. The evolution of postsurgery pain is therefore of interest for future patient management in terms of possible prognoses for distinct groups of patients to enable better patient information. OBJECTIVE(S): An analysis aimed to identify subgroups of patients who share similar time courses of postoperative persistent pain. DESIGN: Prospective cohort study. SETTING: Helsinki University Hospital, Finland, between 2006 and 2010. PATIENTS: A total of 763 women treated for breast cancer at the Helsinki University Hospital. INTERVENTIONS: Employing a data science approach in a nonredundant reanalysis of data published previously, pain ratings acquired at 6, 12, 24 and 36 months after breast cancer surgery, were analysed for a group structure of the temporal courses of pain. Unsupervised automated evolutionary (genetic) algorithms were used for patient cluster detection in the pain ratings and for Gaussian mixture modelling of the slopes of the linear relationship between pain ratings and acquisition times. MAIN OUTCOME MEASURES: Clusters or groups of patients sharing patterns in the time courses of pain between 6 and 36 months after breast cancer surgery. RESULTS: Three groups of patients with distinct time courses of pain were identified as the best solutions for both clustering of the pain ratings and multimodal modelling of theAbstract : BACKGROUND: Persistent pain extending beyond 6 months after breast cancer surgery when adjuvant therapies have ended is a recognised phenomenon. The evolution of postsurgery pain is therefore of interest for future patient management in terms of possible prognoses for distinct groups of patients to enable better patient information. OBJECTIVE(S): An analysis aimed to identify subgroups of patients who share similar time courses of postoperative persistent pain. DESIGN: Prospective cohort study. SETTING: Helsinki University Hospital, Finland, between 2006 and 2010. PATIENTS: A total of 763 women treated for breast cancer at the Helsinki University Hospital. INTERVENTIONS: Employing a data science approach in a nonredundant reanalysis of data published previously, pain ratings acquired at 6, 12, 24 and 36 months after breast cancer surgery, were analysed for a group structure of the temporal courses of pain. Unsupervised automated evolutionary (genetic) algorithms were used for patient cluster detection in the pain ratings and for Gaussian mixture modelling of the slopes of the linear relationship between pain ratings and acquisition times. MAIN OUTCOME MEASURES: Clusters or groups of patients sharing patterns in the time courses of pain between 6 and 36 months after breast cancer surgery. RESULTS: Three groups of patients with distinct time courses of pain were identified as the best solutions for both clustering of the pain ratings and multimodal modelling of the slopes of their temporal trends. In two clusters/groups, pain decreased or remained stable and the two approaches suggested/identified similar subgroups representing 80/763 and 86/763 of the patients, respectively, in whom rather high pain levels tended to further increase over time. CONCLUSION: In the majority of patients, pain after breast cancer surgery decreased rapidly and disappeared or the intensity decreased over 3 years. However, in about a tenth of patients, moderate-to-severe pain tended to increase during the 3-year follow-up. … (more)
- Is Part Of:
- European journal of anaesthesiology. Volume 37:Issue 3(2020:Mar.)
- Journal:
- European journal of anaesthesiology
- Issue:
- Volume 37:Issue 3(2020:Mar.)
- Issue Display:
- Volume 37, Issue 3 (2020)
- Year:
- 2020
- Volume:
- 37
- Issue:
- 3
- Issue Sort Value:
- 2020-0037-0003-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-03
- Subjects:
- Anesthesiology -- Periodicals
Anesthesiology -- Periodicals
Anesthésiologie -- Périodiques
Anesthesiology
Periodicals
Electronic journals
617.96 - Journal URLs:
- http://journals.lww.com/ejanaesthesiology/pages/default.aspx ↗
http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1365-2346/issues ↗
http://www.blackwell-synergy.com/member/institutions/issuelist.asp?journal=eja ↗
http://ovidsp.ovid.com/ovidweb.cgi?T=JS&MODE=ovid&PAGE=toc&D=ovft&AN=00003643-000000000-00000 ↗
http://journals.lww.com ↗
http://www.lww.com/Product/0265-0215 ↗ - DOI:
- 10.1097/EJA.0000000000001116 ↗
- Languages:
- English
- ISSNs:
- 0265-0215
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- Legaldeposit
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