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J Gynecol Oncol. 2017 Mar;28(2):e9. English. Original Article. https://doi.org/10.3802/jgo.2017.28.e9
Kim SI , Kim N , Lee S , Lee S , Joo J , Seo SS , Chung SH , Park SY , Lim MC .
Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, Korea.
Center for Uterine Cancer, Research Institute and Hospital, National Cancer Center, Goyang, Korea. gynlim@gmail.com
Department of Statistics, Dongguk University School of Medicine, Seoul, Korea.
Bio Medical Laboratory Science, Yonsei University Wonju College of Medicine, Wonju, Korea.
Biometric Research Branch, Research Institute and Hospital, National Cancer Center, Goyang, Korea.
Rehabilitation Clinic, Research Institute and Hospital, National Cancer Center, Goyang, Korea.
Gynecologic Cancer Branch, Research Institute and Hospital, National Cancer Center, Goyang, Korea.
Abstract

OBJECTIVE: The Gynecologic Cancer Lymphedema Questionnaire (GCLQ) was designed to identify gynecologic cancer patients with lower limb lymphedema (LLL). The questionnaire consists of 20 items distributed over 7 symptom clusters. The present study aimed to develop an abridged form of the GCLQ for simpler screening and more effective follow-up of LLL. METHODS: Data that had been collected for the development and validation of the Korean version of the GCLQ (GCLQ-K) were used in this study. Receiver-operating characteristic (ROC) curves were drawn according to the individual items of the GCLQ-K. Based on discrimination ability, the candidate items were selected in each symptom cluster. After combining the items, the best model was identified and named GCLQ-7. The area under the ROC curve (AUC) was compared between the GCLQ-7 and the original GCLQ-K. RESULTS: In total, 11 candidate items were selected from the original GCLQ-K. Among the models made with the candidate items, GCLQ-7, the best model, was constructed with 7 items as follows: 1) limited knee movement, 2) general swelling, 3) redness, 4) firmness/tightness, 5) groin swelling, 6) heaviness, and 7) aching. This model exhibited an AUC of 0.945 (95% confidence interval [CI], 0.900–0.991), which is comparable with that of the original GCLQ-K (AUC, 0.867; 95% CI, 0.779–0.956). The best cutoff value was 2 points, at which the sensitivity and specificity were 97.0% and 76.5%, respectively. CONCLUSION: The newly developed short version model, GCLQ-7, showed acceptable discrimination ability as compared with the original GCLQ-K.

Copyright © 2019. Korean Association of Medical Journal Editors.