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Storey S, Luo X, Ofner S, Perkins SM, Von Ah D. The role of glycemic control and symptoms and symptom clusters in breast cancer survivors with type 2 diabetes. Support Care Cancer 2025; 33:371. [PMID: 40210821 PMCID: PMC11985596 DOI: 10.1007/s00520-025-09434-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2024] [Accepted: 04/03/2025] [Indexed: 04/12/2025]
Abstract
PURPOSE The purpose of the study was to describe the type and number of symptoms and examine symptom clusters of breast cancer survivors (BCS) with diabetes (type 2) by glycemic control (HbA1c < 7 or ≥ 7%). METHODS A retrospective cohort study was conducted. Symptom data were extracted from clinical notes in the electronic health record. BCS (stage I-III) diagnosed between 2007 and 2019 had diabetes, and at least one HbA1c within 8 months of initial chemotherapy was included. Zero-inflated negative binomial regression analysis was used to examine total symptoms by glycemic control. Exploratory factor analysis was conducted to identify symptom clusters. RESULTS Three hundred twenty-seven BCS met the inclusion criteria. Two symptom clusters were identified in BCS with HbA1c ≥ 7%: a psychoneurological cluster (anxiety, fatigue, peripheral neuropathy, and depression) and a gastrointestinal cluster (vomiting, nausea, and constipation). Two symptom clusters were identified in BCS with HbA1c < 7% a mixed gastrointestinal/psychoneurological cluster (vomiting, nausea, peripheral neuropathy, fatigue, and constipation) and a mental health symptom cluster (depression and anxiety). CONCLUSION The symptom clusters of BCS differed by glycemic control. Prospective research studies are needed to examine the role of glycemic control in symptoms in BCS with diabetes. Understanding the influence of glycemic control can help providers identify BCS at high risk for troublesome symptoms and symptom clusters, thereby facilitating interventions that target glycemic control, potentially mitigating symptoms, and symptom clusters, and improving outcomes for BCS with diabetes.
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Affiliation(s)
- Susan Storey
- Indiana University School of Nursing, Indianapolis, IN, 46260, USA.
| | - Xiao Luo
- Department of Management Science and Information Systems, School of Business, Oklahoma State University, Stillwater, OK, USA
| | - Susan Ofner
- Department of Biostatistics and Health Data Science, School of Medicine and Richard M. Fairbanks School of Public Health, Indiana University, 410 W 10 th Street, Suite 3000, Indianapolis, IN, 46202, USA
| | - Susan M Perkins
- Department of Biostatistics and Health Data Science, School of Medicine and Richard M. Fairbanks School of Public Health, Indiana University, 410 W 10 th Street, Suite 3000, Indianapolis, IN, 46202, USA
| | - Diane Von Ah
- Cancer Research, Center for Healthy Aging, Self-Management and Complex Care, College of Nursing, The Ohio State University (OSU), 394 Newton Hall, 1585 Neil Avenue, Columbus, OH, 43210, USA
- Comprehensive Cancer Center, Cancer Control Program, OSU, 394 Newton Hall, 1585 Neil Avenue, Columbus, OH, 43210, USA
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Adam R, Vieira R, Hannaford PC, Martin K, Whitaker KL, Murchie P, Elliott AM. Relationship between symptoms, sociodemographic factors, and general practice help-seeking in 10 904 adults aged 50 and over. Eur J Public Health 2025; 35:26-34. [PMID: 39675047 PMCID: PMC11832149 DOI: 10.1093/eurpub/ckae198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2024] Open
Abstract
Symptoms are a common reason for contact with primary care. This study investigated associations between symptom-related, demographic, social, and economic factors on general practice (GP) help-seeking. Secondary analysis of responses to a 25-symptom questionnaire, from 10 904 adults aged ≥50 years reporting at least one symptom in the preceding year. Cluster analysis and univariable and multivariable logistic regressions explored associations between self-reported GP help-seeking, symptom-related factors, and respondent characteristics. Most respondents, 7638 (70%), reported more than one symptom in the preceding year. Ten symptom clusters were identified. Most included common symptoms like headache and back or joint pain. There were increased odds of help-seeking in females, those with poorer health status and those unable to work due to illness/disability when multiple symptoms were reported, but not when single symptoms were reported. Age and sex had variable effects on help-seeking, depending on the symptom. Reporting poorer health status, more comorbidities, and being unable to work due to illness or disability increased odds of help-seeking across a diverse variety of symptoms. Single people and those reporting lower social contact had lower odds of help-seeking for some symptoms. Being a current smoker reduced odds of help-seeking for persistent indigestion/heartburn, persistent cough, coughing up phlegm, and shortness of breath. Factors associated with self-reported help-seeking vary for different symptoms. Poorer health and adverse economic and social factors are associated with increased GP help-seeking. These wider determinants of health interact with symptom experiences and will influence GP workload.
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Affiliation(s)
- Rosalind Adam
- Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, United Kingdom
| | - Rute Vieira
- Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, United Kingdom
| | - Philip C Hannaford
- Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, United Kingdom
| | - Kathryn Martin
- Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, United Kingdom
| | | | - Peter Murchie
- Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, United Kingdom
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Harris C, Hammer MJ, Conley YP, Paul SM, Cooper BA, Shin J, Oppegaard K, Morse L, Levine JD, Miaskowski C. Impact of Multimorbidity on Symptom Burden and Symptom Clusters in Patients Receiving Chemotherapy. Cancer Med 2025; 14:e70418. [PMID: 39910913 PMCID: PMC11799588 DOI: 10.1002/cam4.70418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2024] [Revised: 10/23/2024] [Accepted: 11/01/2024] [Indexed: 02/07/2025] Open
Abstract
BACKGROUND Detailed information on patient characteristics and symptom burden associated with multimorbidity in oncology patients is extremely limited. Purposes were to determine the prevalence of low (≤ 2) and high (≥ 3) multimorbidity in a sample of oncology outpatients (n = 1343) undergoing chemotherapy and evaluate for differences between the two multimorbidity groups in demographic and clinical characteristics; the occurrence, severity, and distress of 38 symptoms; and the stability and consistency of symptom clusters. METHODS Using the Self-Administered Comorbidity Questionnaire, patients were classified into low and high multimorbidity groups. Memorial Symptom Assessment Scale was used to assess the occurrence, severity, and distress of 38 symptoms prior to the patients' second or third cycle of chemotherapy. For each multimorbidity group, symptom clusters based on occurrence rates were identified using exploratory factor analysis. RESULTS Compared to the low group (61.4%), patients in the high group (38.6%) were older, had fewer years of education, were less likely to be married or partnered, less likely to be employed, and had a lower annual income. In addition, they had a higher body mass index, poorer functional status, were a longer time since their cancer diagnosis, and were more likely to have received previous cancer treatments and have metastatic disease. Patients in the low and high groups reported 12.7 (±6.7) and 15.9 (±7.5) concurrent symptoms, respectively. Eight and seven symptom clusters were identified for the low and high groups, respectively. Psychological, gastrointestinal, weight gain, hormonal, and respiratory clusters were stable across multimorbidity groups. Weight gain and respiratory clusters were consistent. Three unstable clusters were identified in the low group and two in the high group. CONCLUSIONS Findings suggest that higher multimorbidity is associated with various social determinants of health and a higher symptom burden. Differences between multimorbidity groups may be related to aging, treatments, and/or comorbid conditions.
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Affiliation(s)
- Carolyn Harris
- School of NursingUniversity of PittsburghPittsburghPennsylvaniaUSA
| | | | - Yvette P. Conley
- School of NursingUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Steven M. Paul
- School of NursingUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Bruce A. Cooper
- School of NursingUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Joosun Shin
- Dana‐Farber Cancer InstituteBostonMassachusettsUSA
| | | | - Lisa Morse
- School of NursingUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Jon D. Levine
- School of MedicineUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Christine Miaskowski
- School of NursingUniversity of CaliforniaSan FranciscoCaliforniaUSA
- School of MedicineUniversity of CaliforniaSan FranciscoCaliforniaUSA
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Lan X, Ji X, Zheng X, Ding X, Mou H, Lu S, Ye B. Socio-demographic and clinical determinants of self-care in adults with type 2 diabetes: a multicenter cross-sectional study in Zhejiang province, China. BMC Public Health 2025; 25:397. [PMID: 39885509 PMCID: PMC11783724 DOI: 10.1186/s12889-025-21622-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Accepted: 01/24/2025] [Indexed: 02/01/2025] Open
Abstract
BACKGROUND Self-care, a process of maintaining health through health-promoting practices and managing illness, is pivotal for the management of type 2 diabetes. This study aimed to explore the self-care level and investigate its socio-demographic and clinical determinants among Chinese adults with type 2 diabetes. METHODS In this multicenter cross-sectional study, we enrolled 495 Chinese adults with type 2 diabetes from the outpatient departments of three tertiary hospitals in Zhejiang province, China. The Self-Care of Diabetes Inventory (SCODI) was used to measure self-care maintenance, self-care monitoring, and self-care management as three critical components of the dynamic self-care process. Self-care self-efficacy is a critical factor affecting the self-care process, which was measured by the SCODI. Multiple quantile regression models were employed to identify the determinants of each self-care component and self-care self-efficacy. RESULTS Participants had a median age of 62 years, of whom 55.4% were male. The median scores for self-care maintenance, self-care monitoring, and self-care management were 66.67 (50.00-85.42), 47.06 (32.35-58.82), and 53.13 (34.38-68.75), respectively, whereas the median score for self-care self-efficacy was 70.45 (52.27-84.09). Living in the southwest of Zhejiang province and having lower self-care self-efficacy were associated with lower self-care maintenance. Female gender, belonging to minorities, having complications, not attending diabetes self-management education in the last year, living in the southwest of Zhejiang province, and having lower self-care self-efficacy were associated with lower self-care monitoring. Having complications, using insulin, living in the southwest of Zhejiang province, and having lower self-care self-efficacy were associated with a lower level of self-care management. Living in the southwest of Zhejiang province was associated with lower self-care self-efficacy. CONCLUSIONS/INTERPRETATION The findings of this study provide invaluable insights into the factors affecting self-care among Chinese adults with type 2 diabetes. By enhancing self-care self-efficacy and participating in diabetes self-management education, healthcare providers can develop tailored self-care interventions to improve diabetes care, particularly for adults with type 2 diabetes who are female, belong to minority groups, have complications, use insulin, or reside in the southwest of Zhejiang province.
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Affiliation(s)
- Xuefen Lan
- Nursing Department, Medicine College, Lishui University, Lishui, Zhejiang, China
| | - Xiaozhen Ji
- Department of Endocrinology, Lishui People's Hospital, Lishui, Zhejiang, China
| | - Xiaojia Zheng
- Department of Endocrinology, Lishui People's Hospital, Lishui, Zhejiang, China
| | - Xiaoyu Ding
- Emergency Medicine Center, Internal Medicine General Ward, Jinhua Municipal Center Hospital, Jinhua, Zhejiang, China
| | - Hongyi Mou
- Hepato-Biliary-Pancreatic Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Shunfei Lu
- Medicine College, Lishui University, Lishui, Zhejiang, China.
| | - Bin Ye
- Department of Endocrinology, Lishui People's Hospital, Lishui, Zhejiang, China.
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Cao T, Brady V, Whisenant M, Wang X, Gu Y, Wu H. Toward Reliable Symptom Coding in Electronic Health Records for Symptom Assessment and Research: Identification and Categorization of International Classification of Diseases, Ninth Revision, Clinical Modification Symptom Codes. Comput Inform Nurs 2024; 42:636-647. [PMID: 38968447 PMCID: PMC11377150 DOI: 10.1097/cin.0000000000001146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/07/2024]
Abstract
To date, symptom documentation has mostly relied on clinical notes in electronic health records or patient-reported outcomes using disease-specific symptom inventories. To provide a common and precise language for symptom recording, assessment, and research, a comprehensive list of symptom codes is needed. The International Classification of Diseases, Ninth Revision or its clinical modification ( International Classification of Diseases, Ninth Revision, Clinical Modification ) has a range of codes designated for symptoms, but it does not contain codes for all possible symptoms, and not all codes in that range are symptom related. This study aimed to identify and categorize the first list of International Classification of Diseases, Ninth Revision, Clinical Modification symptom codes for a general population and demonstrate their use to characterize symptoms of patients with type 2 diabetes mellitus in the Cerner database. A list of potential symptom codes was automatically extracted from the Unified Medical Language System Metathesaurus. Two clinical experts in symptom science and diabetes manually reviewed this list to identify and categorize codes as symptoms. A total of 1888 International Classification of Diseases, Ninth Revision, Clinical Modification symptom codes were identified and categorized into 65 categories. The symptom characterization using the newly obtained symptom codes and categories was found to be more reasonable than that using the previous symptom codes and categories on the same Cerner diabetes cohort.
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Affiliation(s)
- Tru Cao
- Author Affiliations: UTHealth Houston School of Public Health (Drs Cao, Wang, and Wu and Mr Gu), UTHealth Houston Cizik School of Nursing (Dr Brady), and The University of Texas MD Anderson Cancer Center (Dr Whisenant)
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Storey S, Luo X, Ren J, Huang K, Von Ah D. Symptom clusters in breast cancer survivors with and without type 2 diabetes over the cancer trajectory. Asia Pac J Oncol Nurs 2024; 11:100343. [PMID: 38222966 PMCID: PMC10784674 DOI: 10.1016/j.apjon.2023.100343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Accepted: 11/10/2023] [Indexed: 01/16/2024] Open
Abstract
Objective This study aimed to investigate symptoms and symptom clusters in breast cancer survivors (BCS) with and without type 2 diabetes across three crucial periods during the cancer trajectory (0-6 months, 12-18 months, and 24-30 months) post-initial chemotherapy. Methods Eight common symptoms in both BCS and individuals with diabetes were identified through natural language processing of electronic health records from January 2007 to December 2018. Exploratory factor analysis was employed to discern symptom clusters, evaluating their stability, consistency, and clinical relevance. Results Among the 4601 BCS in the study, 20% (n = 905) had a diabetes diagnosis. Gastrointestinal symptoms and fatigue were prevalent in both groups. While BCS in both groups exhibited an equal number of clusters, the composition of these clusters differed. Symptom clusters varied over time between BCS with and without diabetes. BCS with diabetes demonstrated less stability (repeated clusters) and consistency (same individual symptoms comprising clusters) than their counterparts without diabetes. This suggests that BCS with diabetes may experience distinct symptom clusters at pivotal points in the cancer treatment trajectory. Conclusions Healthcare providers must be attentive to BCS with diabetes throughout the cancer trajectory, considering intensified and/or unique profiles of symptoms and symptom clusters. Interdisciplinary cancer survivorship models are essential for effective diabetes management in BCS. Implementing a comprehensive diabetes management program throughout the cancer trajectory could alleviate symptoms and symptom clusters, ultimately enhancing health outcomes and potentially reducing healthcare resource utilization.
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Affiliation(s)
- Susan Storey
- Indiana University School of Nursing, Indianapolis, IN, USA
| | - Xiao Luo
- Department of Management Science and Information Systems, School of Business, Oklahoma State University, OK, USA
| | - Jie Ren
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine Indianapolis, IN, USA
| | - Kun Huang
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine; Regenstrief Institute, Indianapolis, IN, USA
| | - Diane Von Ah
- College of Nursing, Cancer Research, Center for Healthy Aging, Self-Management and Complex Care, The Ohio State University, Columbus, OH, USA
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