Heterogeneity in resilience patterns and its prediction of 1-year quality of life outcomes among patients with newly diagnosed cancer: An exploratory piecewise growth mixture model analysis

作者全名："Liang, Mu Zi; Liu, Mei Ling; Tang, Ying; Molassiotis, Alex; Knobf, M. Tish; Chen, Peng; Hu, Guang Yun; Sun, Zhe; Yu, Yuan Liang; Ye, Zeng Jie"

作者地址："[Liang, Mu Zi] Guangdong Acad Populat Dev, Guangzhou, Peoples R China; [Liu, Mei Ling] Sun Yat Sen Univ, Canc Ctr, Collaborat Innovat Ctr Canc Med, State Key Lab Oncol South China, Guangzhou, Peoples R China; [Tang, Ying] Guangzhou Univ Chinese Med, Inst Tumor, Guangzhou, Peoples R China; [Molassiotis, Alex] Univ Derby, Coll Arts Humanities & Educ, Derby, England; [Knobf, M. Tish] Yale Univ, Sch Nursing, Orange, CT USA; [Chen, Peng] Guizhou Univ Tradit Chinese Med, Basic Med Sch, Guiyang, Peoples R China; [Hu, Guang Yun] Army Med Univ, Chongqing, Peoples R China; [Sun, Zhe] Guangzhou Univ Chinese Med, Affiliated Hosp 1, Guangzhou, Peoples R China; [Yu, Yuan Liang] South China Univ Technol, Guangzhou, Peoples R China; [Ye, Zeng Jie] Guangzhou Univ Chinese Med, Sch Nursing, Guangzhou, Guangdong, Peoples R China"

通信作者："Ye, ZJ (通讯作者)，Guangzhou Univ Chinese Med, Sch Nursing, Guangzhou, Guangdong, Peoples R China."

来源：EUROPEAN JOURNAL OF ONCOLOGY NURSING

ESI学科分类：CLINICAL MEDICINE

WOS号：WOS:001050073800001

JCR分区：Q1

影响因子：2.7

年份：2023

卷号：66

期号：　

开始页：　

结束页：　

文献类型：Article

关键词：Resilience; Heterogeneity; Patterns; Growth; Newly diagnosed cancer; Exploratory; Piecewise growth mixture model analysis; Psycho-oncology; Quality of life

摘要："Purpose: This study was designed to explore the impact of a new cancer diagnosis on resilience of patients and whether the resilience patterns could predict Quality of Life (QoL) in the first year.Methods: An exploratory linear piecewise growth mixture modeling (PGMM) with one hypothetical dot (3 months since diagnosis, T1) was employed to identify different resilience patterns and growth in 289 patients with different cancer diagnoses at five assessment occasions (T0-T4). Logistic regression analysis was performed to select potential predictors and receiver operating characteristic (ROC) curve analysis was utilized to test PGMM's discriminative ability against 1-year QoL.Results: Five discrete resilience trajectories with two growing trends were identified, including ""Transcendence"" (7.3%), ""Resilient"" (47.4%), ""Recovery"" (18.7%), ""Damaged"" (14.9%) and ""Maladaption"" (11.8%). Advanced stage, colorectal cancer, and receiving surgery therapy were significant predictors of negative resilience tra-jectories (""Damaged"" or ""Maladaption""). Discriminative ability was good for PGMM (AUC = 0.81, 95%CI, 0.76-0.85, P < 0.0001).Conclusion: Heterogeneity is identified in resilience growth before and after 3 months since diagnosis. 26.7% newly diagnosed patients need additional attention especially for those with advanced colorectal cancer and receiving surgery therapy."

基金机构："National Natural Science Foundation of China [72274043, 71904033]; Young Elite Scientists Sponsorship Program by CACM [2021-QNRC2-B08]; Humanity and Social Science Foundation of Department of Education of Guangdong Province [2020WTSCX009]; Science and Technology Projects in Guangzhou [202102020108]"

基金资助正文："This research was funded by grants from National Natural Science Foundation of China (Nos. 72274043, 71904033) , Young Elite Scientists Sponsorship Program by CACM (No. 2021-QNRC2-B08) , Humanity and Social Science Foundation of Department of Education of Guangdong Province (No. 2020WTSCX009) and Science and Technology Projects in Guangzhou (No. 202102020108) ."