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Prediction of quality-adjusted life years (QALYs) after bariatric surgery using regularized linear regression models : results from a Swedish nationwide quality register

Sun, Sun (author)
Umeå universitet,Institutionen för epidemiologi och global hälsa
Stenberg, Erik, 1979- (author)
Örebro universitet,Institutionen för medicinska vetenskaper,Region Örebro län,Department of Surgery, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
Lindholm, Lars (author)
Umeå universitet,Institutionen för epidemiologi och global hälsa
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Sahlen, Klas-Göran, 1957- (author)
Umeå universitet,Institutionen för epidemiologi och global hälsa
Franklin, Karl A. (author)
Umeå universitet,Institutionen för kirurgisk och perioperativ vetenskap
Luo, Nan (author)
Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
Cao, Yang, Associate Professor, 1972- (author)
Örebro universitet,Institutionen för medicinska vetenskaper,Region Örebro län,Clinical Epidemiology and Biostatistics, School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden; Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, 171 77, Stockholm, Sweden
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 (creator_code:org_t)
Springer, 2023
2023
English.
In: Obesity Surgery. - : Springer. - 0960-8923 .- 1708-0428. ; 33:8, s. 2452-2462
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • PURPOSE: To investigate whether the quality-adjusted life years (QALYs) of the patients who underwent bariatric surgery could be predicted using their baseline information.MATERIALS AND METHODS: All patients who received bariatric surgery in Sweden between January 1, 2011 and March 31, 2019 were obtained from the Scandinavian Obesity Surgery Registry (SOReg). Baseline information included patients' sociodemographic characteristics, details regarding the procedure, and postsurgical conditions. QALYs were assessed by the SF-6D at follow-up years 1 and 2. The general and regularized linear regression models were used to predict postoperative QALYs.RESULTS: All regression models demonstrated satisfactory and comparable performance in predicting QALYs at follow-up year 1, with R2 and relative root mean squared error (RRMSE) values of about 0.57 and 9.6%, respectively. The performance of the general linear regression model increased with the number of variables; however, the improvement was ignorable when the number of variables was more than 30 and 50 for follow-up years 1 and 2, respectively. Although minor L1 and L2 regularization provided better prediction ability, the improvement was negligible when the number of variables was more than 20. All the models showed poorer performance for predicting QALYs at follow-up year 2.CONCLUSIONS: Patient characteristics before bariatric surgery including health related quality of life, age, sex, BMI, postoperative complications within six weeks, and smoking status, may be adequate in predicting their postoperative QALYs after one year. Understanding these factors can help identify individuals who require more personalized and intensive support before, during, and after surgery.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Kirurgi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Surgery (hsv//eng)
MEDICIN OCH HÄLSOVETENSKAP  -- Hälsovetenskap -- Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Health Sciences -- Public Health, Global Health, Social Medicine and Epidemiology (hsv//eng)

Keyword

Bariatric surgery
Prediction
Quality-adjusted life years
Real-world data
SF-6D

Publication and Content Type

ref (subject category)
art (subject category)

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