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Ma H, Hu K, Wu W, Wu Q, Ye Q, Jiang X, Tang L, He Y, Yang Q. Illness perception profile among cancer patients and its influencing factors: A cross-sectional study. Eur J Oncol Nurs 2024; 69:102526. [PMID: 38401348 DOI: 10.1016/j.ejon.2024.102526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Revised: 02/01/2024] [Accepted: 02/04/2024] [Indexed: 02/26/2024]
Abstract
PURPOSE The purpose of this study was to explore latent profiles of illness perception among cancer patients and its influencing factors. METHODS This study was a cross-sectional study adopting convenience sampling to select cancer patients from two hospitals in China. A total of 286 patients completed Brief Illness Perception Questionnaire, Post-traumatic Growth Inventory, Fear of Disease Progression Questionnaire and Psychosocial Adjustment to Illness Scale. Latent profile analysis and multiple linear regression were performed to explore the subgroups and factors influencing classification. RESULTS Three subgroups were identified, which were labelled as "Moderate Illness Perception Group" (16.8%; C1), "High Illness Perception with Heightened Concerns Group" (68.5%; C2) and "High Resilience and Low Symptomatic Impact Group" (14.7%; C3). Specifically, "Normal", "Mild symptom" and "Bed time during the day <50%" of "Functional Status" were more associated with C3. "Worker", "Farmer" and "Self-employed" were more associated with C1 and C2. Patients who had more "knowledge of the disease" were more associated with C2 and C3, who had less "post-traumatic growth" were more associated with C1, and who had less "fear of disease progression" and more "psychosocial adjustment" were more associated with C3 (all P < 0.05). CONCLUSIONS There was significant variability of illness perception among three subgroups of cancer patients, which emphasized the complexity of psychological condition. The insights derived from these distinct profiles enables tailored interventions and patient-centered communication strategies. However, integrating objective measures or biomarkers is needed to complement self-reported data.
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Affiliation(s)
- Hualong Ma
- School of Nursing, Jinan University, Guangdong, China
| | - Ke Hu
- School of Nursing, Jinan University, Guangdong, China
| | - Weixin Wu
- St. Mark's School, 25 Marlboro Road Southborough, MA, USA
| | - Qinyang Wu
- School of Nursing, Jinan University, Guangdong, China
| | - Qiuyun Ye
- Tianhe Shipai Huashi Community Health Service Center, Guangdong, China
| | | | - Lu Tang
- Shanwei Second People's Hospital, Guangdong, China
| | - Yongyue He
- Shanwei Second People's Hospital, Guangdong, China.
| | - Qiaohong Yang
- School of Nursing, Jinan University, Guangdong, China.
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Zhao Q, Small DS, Ertefaie A. Selective inference for effect modification via the lasso. J R Stat Soc Series B Stat Methodol 2021; 84:382-413. [DOI: 10.1111/rssb.12483] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Affiliation(s)
- Qingyuan Zhao
- Department of Pure Mathematics and Mathematical Statistics University of Cambridge Cambridge UK
| | - Dylan S. Small
- Department of Statistics and Data Science University of Pennsylvania Philadelphia Pennsylvania USA
| | - Ashkan Ertefaie
- Department of Biostatistics and Computational Biology University of Rochester Rochester New York USA
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Heng S, Kang H, Small DS, Fogarty CB. Increasing power for observational studies of aberrant response: An adaptive approach. J R Stat Soc Series B Stat Methodol 2021. [DOI: 10.1111/rssb.12424] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Affiliation(s)
- Siyu Heng
- University of Pennsylvania Philadelphia PA USA
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Issa AM, Carleton B, Gerhard T, Filipski KK, Freedman AN, Kimmel S, Liu G, Longo C, Maitland-van der Zee AH, Sansbury L, Zhou W, Bartlett G. Pharmacoepidemiology: A time for a new multidisciplinary approach to precision medicine. Pharmacoepidemiol Drug Saf 2021; 30:985-992. [PMID: 33715268 DOI: 10.1002/pds.5226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2020] [Accepted: 03/09/2021] [Indexed: 11/06/2022]
Abstract
The advent of the genomic age has created a rapid increase in complexity for the development and selection of drug treatments. A key component of precision medicine is the use of genetic information to improve therapeutic effectiveness of drugs and prevent potential adverse drug reactions. Pharmacoepidemiology, as a field, uses observational methods to evaluate the safety and effectiveness of drug treatments in populations. Pharmacoepidemiology by virtue of its focus, tradition, and research orientation can provide appropriate study designs and analysis methods for precision medicine. The objective of this manuscript is to demonstrate how pharmacoepidemiology can impact and shape precision medicine and serve as a reference for pharmacoepidemiologists interested in contributing to the science of precision medicine. This paper depicts the state of the science with respect to the need for pharmacoepidemiology and pharmacoepidemiological methods, tools and approaches for precision medicine; the need for and how pharmacoepidemiologists use their skills to engage with the precision medicine community; and recommendations for moving the science of precision medicine pharmacoepidemiology forward. We propose a new integrated multidisciplinary approach dedicated to the emerging science of precision medicine pharmacoepidemiology.
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Affiliation(s)
- Amalia M Issa
- Personalized Precision Medicine & Targeted Therapeutics, Springfield, Pennsylvania, USA.,'Pharmaceutical Sciences' and 'Health Policy', University of the Sciences in Philadelphia, Philadelphia, Pennsylvania, USA.,'Family Medicine' and `Centre of Genomics & Policy'; Faculty of Medicine & Health Sciences, McGill University, Montreal, Quebec, Canada
| | - Bruce Carleton
- Division of Translational Therapeutics, Department of Pediatrics, Faculty of Medicine, University of British Columbia, and BC Children's Hospital and Research Institute, Vancouver, British Columbia, Canada
| | - Tobias Gerhard
- Center for Pharmacoepidemiology and Treatment Science, Rutgers University, New Brunswick, New Jersey, USA
| | - Kelly K Filipski
- Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, Maryland, USA
| | - Andrew N Freedman
- Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, Maryland, USA
| | - Stephen Kimmel
- 'College of Public Health & Health Professions' and 'College of Medicine', University of Florida, Gainesville, Florida, USA
| | - Geoffrey Liu
- Epidemiology; Dalla Lana School of Public Health, Princess Margaret Cancer Centre and University of Toronto, Toronto, Ontario, Canada
| | - Cristina Longo
- Respiratory Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Anke H Maitland-van der Zee
- Respiratory Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Leah Sansbury
- Epidemiology, Value Evidence and Outcomes, GlaxoSmithKline, Research Triangle Park, North Carolina, USA
| | - Wei Zhou
- Center for Observational and Real-world Evidence, Merck & Co., Inc., Kenilworth, New Jersey, USA
| | - Gillian Bartlett
- School of Medicine, University of Missouri, Columbia, Missouri, USA
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Karmakar B, Small DS. Assessment of the extent of corroboration of an elaborate theory of a causal hypothesis using partial conjunctions of evidence factors. Ann Stat 2020. [DOI: 10.1214/19-aos1929] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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Cui Y, Tchetgen ET. A semiparametric instrumental variable approach to optimal treatment regimes under endogeneity. J Am Stat Assoc 2020; 116:162-173. [PMID: 33994604 PMCID: PMC8118566 DOI: 10.1080/01621459.2020.1783272] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2019] [Revised: 02/05/2020] [Accepted: 06/09/2020] [Indexed: 01/23/2023]
Abstract
There is a fast-growing literature on estimating optimal treatment regimes based on randomized trials or observational studies under a key identifying condition of no unmeasured confounding. Because confounding by unmeasured factors cannot generally be ruled out with certainty in observational studies or randomized trials subject to noncompliance, we propose a general instrumental variable approach to learning optimal treatment regimes under endogeneity. Specifically, we establish identification of both value function E [ Y D ( L ) ] for a given regime D and optimal regimes arg max D E [ Y D ( L ) ] with the aid of a binary instrumental variable, when no unmeasured confounding fails to hold. We also construct novel multiply robust classification-based estimators. Furthermore, we propose to identify and estimate optimal treatment regimes among those who would comply to the assigned treatment under a monotonicity assumption. In this latter case, we establish the somewhat surprising result that complier optimal regimes can be consistently estimated without directly collecting compliance information and therefore without the complier average treatment effect itself being identified. Our approach is illustrated via extensive simulation studies and a data application on the effect of child rearing on labor participation.
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Affiliation(s)
- Yifan Cui
- Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, PA 19104
| | - Eric Tchetgen Tchetgen
- Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, PA 19104
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Harris RA, Kranzler HR, Chang KM, Doubeni CA, Gross R. Long-term use of hydrocodone vs. oxycodone in primary care. Drug Alcohol Depend 2019; 205:107524. [PMID: 31707268 PMCID: PMC9338763 DOI: 10.1016/j.drugalcdep.2019.06.026] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/09/2019] [Revised: 05/20/2019] [Accepted: 06/19/2019] [Indexed: 12/20/2022]
Abstract
BACKGROUND Hydrocodone and oxycodone are the Schedule II opioids most often prescribed in primary care. Notwithstanding the dangers of prescription opioid use, the likelihood of long-term use with either drug is presently unknown. METHODS Using a retrospective cohort design and data from a commerical healthcare claims repository, we compared the likelihood of long-term use of hydrocodone and oxycodone in primary care patients presenting with acute back pain. Treatment was categorized as long-term if the prescription dates spanned ≥90 days from initial prescription to the run-out date of the last prescription, and included ≥120 days' supply or ≥10 fills. Instrumental variable methods and probit regression were used to model the effect of drug choice on long-term use, estimate the average treatment effect, and correct for confounding by indication. RESULTS A total of 3,983 patients who were prescribed only hydrocodone or only oxycodone were followed for 270 days in 2016. Long-term opioid use was observed in 320 patients (8%). Controlling for potential confounders including morphine milligram equivalents and dosage, an estimated 12% (95 CI, 10%-14%) treated with hydrocodone transitioned to long-term use vs. 2% (95 CI, 1%-3%) on oxycodone. Among patients who received more than one prescription (n = 1,866), an estimated 23% (95 CI, 19%-26%) treated with hydrocodone transitioned to long-term use vs. 5% (95 CI, 3%-7%) on oxycodone. The difference between drugs was supported in sensitivity and subgroup analyses. Sample selection bias was not detected. CONCLUSIONS Long-term use was substantially greater for patients treated with hydrocodone than oxycodone, despite equianalgesia.
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Affiliation(s)
- Rebecca Arden Harris
- Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
| | - Henry R Kranzler
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States; VISN 4 Mental Illness Research, Education and Clinical Center, The Corporal Michael Crescenz VA Medical Center, United States
| | - Kyong-Mi Chang
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States; The Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania, United States
| | - Chyke A Doubeni
- Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Robert Gross
- Department of Medicine, Infectious Diseases, Department of Epidemiology, Biostatistics, Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
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Ertefaie A, Nguyen A, Harding DJ, Morenoff JD, Yang W. Instrumental variable analysis with censored data in the presence of many weak instruments: Application to the effect of being sentenced to prison on time to employment. Ann Appl Stat 2018. [DOI: 10.1214/18-aoas1174] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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