{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T06:31:25Z","timestamp":1787725885673,"version":"build-2784847793"},"reference-count":20,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T00:00:00Z","timestamp":1787702400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Symptom burden among breast cancer patients receiving postoperative chemotherapy shows marked individual variability, yet its longitudinal trajectory has not been fully characterized.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Aim<\/jats:title>\n                    <jats:p>To delineate heterogeneous trajectories of symptom burden and identify their influencing factors in postoperative breast cancer patients undergoing chemotherapy.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We recruited postoperative breast cancer patients receiving chemotherapy from a tertiary hospital in Ningxia, China. Participants completed a general information questionnaire and the Chinese version of the M. D. Anderson Symptom Inventory (MDASI-C) at five time points: T1 (3\u202fdays post-surgery), T2 (14\u202fdays post-surgery), T3 (1\u20133\u202fdays before the first chemotherapy session), T4 (7\u201314\u202fdays after the 4th chemotherapy session), and T5 (7\u201314\u202fdays after the 8th chemotherapy session). We applied latent class growth models to identify distinct symptom burden trajectories and used logistic regression to examine factors associated with trajectory membership.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Three distinct trajectories of symptom burden were identified: the high-risk group (\n                      <jats:italic>n<\/jats:italic>\n                      \u202f=\u202f18, 8.1%), the steadily increasing group (\n                      <jats:italic>n<\/jats:italic>\n                      \u202f=\u202f154, 67.3%), and the gradually improving group (\n                      <jats:italic>n<\/jats:italic>\n                      \u202f=\u202f53, 24.6%). Multinomial logistic regression analysis, using the gradually improving group as the reference, indicated that employment status (OR\u202f=\u202f0.464, 95% CI: 0.234\u20130.922,\n                      <jats:italic>p<\/jats:italic>\n                      \u202f=\u202f0.028) and a higher level of disease-related knowledge (OR\u202f=\u202f0.351, 95% CI: 0.161\u20130.764,\n                      <jats:italic>p<\/jats:italic>\n                      \u202f=\u202f0.008) serve as protective factors against adverse symptom burden trajectories.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>There is notable heterogeneity within the population regarding symptom burden trajectories. In comparison to patients in the gradually improving group, those who are employed and possess a higher level of disease-related knowledge are significantly less likely to be classified within the steadily increasing group. Clinicians should prioritize the early identification of high-risk populations, engage in dynamic symptom monitoring, and implement precision management strategies based on trajectory classifications to mitigate symptom burden and enhance quality of life.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpubh.2026.1909654","type":"journal-article","created":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T06:03:16Z","timestamp":1787724196000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A longitudinal analysis of symptom burden trajectories among breast cancer patients undergoing postoperative chemotherapy and related factors: a latent class growth model"],"prefix":"10.3389","volume":"14","author":[{"given":"Wanqin","family":"Tie","sequence":"first","affiliation":[{"name":"General Hospital of Ningxia Medical University","place":["Yinchuan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xi","family":"Zhang","sequence":"additional","affiliation":[{"name":"General Hospital of Ningxia Medical University","place":["Yinchuan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liang","family":"Yue","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University School of Medicine","place":["Shanghai, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lingling","family":"Yang","sequence":"additional","affiliation":[{"name":"General Hospital of Ningxia Medical University","place":["Yinchuan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meng","family":"Niu","sequence":"additional","affiliation":[{"name":"General Hospital of Ningxia Medical University","place":["Yinchuan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiayi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Ningxia Medical University School of Nursing","place":["Yinchuan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,8,26]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"209","DOI":"10.3322\/caac.21660","article-title":"Global cancer statistics 2020: Globocan estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"71","author":"Sung","year":"2021","journal-title":"CA Cancer J Clin"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"900","DOI":"10.20892\/j.issn.2095-3941.2020.0523","article-title":"Breast cancer incidence and mortality in women in China: temporal trends and projections to 2030","volume":"18","author":"Lei","year":"2021","journal-title":"Cancer Biol Med"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"1281","DOI":"10.2147\/PRBM.S315930","article-title":"Type C behavior and associated factors in patients with breast cancer during 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