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Wojcik KM, Kamil D, Zhang J, Wilson OWA, Smith L, Butera G, Isaacs C, Kurian A, Jayasekera J. A scoping review of web-based, interactive, personalized decision-making tools available to support breast cancer treatment and survivorship care. J Cancer Surviv 2024:10.1007/s11764-024-01567-6. [PMID: 38538922 PMCID: PMC11436482 DOI: 10.1007/s11764-024-01567-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Accepted: 03/12/2024] [Indexed: 09/29/2024]
Abstract
PURPOSE We reviewed existing personalized, web-based, interactive decision-making tools available to guide breast cancer treatment and survivorship care decisions in clinical settings. METHODS The study was conducted using the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). We searched PubMed and related databases for interactive web-based decision-making tools developed to support breast cancer treatment and survivorship care from 2013 to 2023. Information on each tool's purpose, target population, data sources, individual and contextual characteristics, outcomes, validation, and usability testing were extracted. We completed a quality assessment for each tool using the International Patient Decision Aid Standard (IPDAS) instrument. RESULTS We found 54 tools providing personalized breast cancer outcomes (e.g., recurrence) and treatment recommendations (e.g., chemotherapy) based on individual clinical (e.g., stage), genomic (e.g., 21-gene-recurrence score), behavioral (e.g., smoking), and contextual (e.g., insurance) characteristics. Forty-five tools were validated, and nine had undergone usability testing. However, validation and usability testing included mostly White, educated, and/or insured individuals. The average quality assessment score of the tools was 16 (range: 6-46; potential maximum: 63). CONCLUSIONS There was wide variation in the characteristics, quality, validity, and usability of the tools. Future studies should consider diverse populations for tool development and testing. IMPLICATIONS FOR CANCER SURVIVORS There are tools available to support personalized breast cancer treatment and survivorship care decisions in clinical settings. It is important for both cancer survivors and physicians to carefully consider the quality, validity, and usability of these tools before using them to guide care decisions.
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Affiliation(s)
- Kaitlyn M Wojcik
- Health Equity and Decision Sciences Research Laboratory, Division of Intramural Research, National Institute On Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Dalya Kamil
- Health Equity and Decision Sciences Research Laboratory, Division of Intramural Research, National Institute On Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, 20892, USA
| | | | - Oliver W A Wilson
- Health Equity and Decision Sciences Research Laboratory, Division of Intramural Research, National Institute On Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Laney Smith
- Frederick P. Whiddon College of Medicine, Mobile, AL, USA
| | - Gisela Butera
- Office of Research Services, National Institutes of Health Library, Bethesda, MD, USA
| | - Claudine Isaacs
- Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC, USA
| | - Allison Kurian
- Departments of Medicine and Epidemiology and Population Health at Stanford University School of Medicine, Stanford, CA, USA
| | - Jinani Jayasekera
- Health Equity and Decision Sciences Research Laboratory, Division of Intramural Research, National Institute On Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, 20892, USA.
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Record SM, Chanenchuk T, Parrish KM, Kaplan SJ, Kimmick G, Plichta JK. Prognostic Tools for Older Women with Breast Cancer: A Systematic Review. MEDICINA (KAUNAS, LITHUANIA) 2023; 59:1576. [PMID: 37763695 PMCID: PMC10534323 DOI: 10.3390/medicina59091576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 08/23/2023] [Accepted: 08/25/2023] [Indexed: 09/29/2023]
Abstract
Background: Breast cancer is the most common cancer in women, and older patients comprise an increasing proportion of patients with this disease. The older breast cancer population is heterogenous with unique factors affecting clinical decision making. While many models have been developed and tested for breast cancer patients of all ages, tools specifically developed for older patients with breast cancer have not been recently reviewed. We systematically reviewed prognostic models developed and/or validated for older patients with breast cancer. Methods: We conducted a systematic search in 3 electronic databases. We identified original studies that were published prior to 8 November 2022 and presented the development and/or validation of models based mainly on clinico-pathological factors to predict response to treatment, recurrence, and/or mortality in older patients with breast cancer. The PROBAST was used to assess the ROB and applicability of each included tool. Results: We screened titles and abstracts of 7316 records. This generated 126 studies for a full text review. We identified 17 eligible articles, all of which presented tool development. The models were developed between 1996 and 2022, mostly using national registry data. The prognostic models were mainly developed in the United States (n = 7; 41%). For the derivation cohorts, the median sample size was 213 (interquartile range, 81-845). For the 17 included modes, the median number of predictive factors was 7 (4.5-10). Conclusions: There have been several studies focused on developing prognostic tools specifically for older patients with breast cancer, and the predictions made by these tools vary widely to include response to treatment, recurrence, and mortality. While external validation was rare, we found that it was typically concordant with interval validation results. Studies that were not validated or only internally validated still require external validation. However, most of the models presented in this review represent promising tools for clinical application in the care of older patients with breast cancer.
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Affiliation(s)
- Sydney M. Record
- Department of Surgery, Duke University Medical Center, Durham, NC 27710, USA
| | - Tori Chanenchuk
- Department of Surgery, Duke University Medical Center, Durham, NC 27710, USA
| | - Kendra M. Parrish
- Department of Surgery, Duke University Medical Center, Durham, NC 27710, USA
| | | | - Gretchen Kimmick
- Duke Cancer Institute, Duke University, Durham, NC 27710, USA
- Department of Medicine, Duke University Medical Center, Durham, NC 27710, USA
| | - Jennifer K. Plichta
- Department of Surgery, Duke University Medical Center, Durham, NC 27710, USA
- Duke Cancer Institute, Duke University, Durham, NC 27710, USA
- Department of Population Health Sciences, Duke University Medical Center, Durham, NC 27710, USA
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Dias-Carvalho A, Ferreira M, Ferreira R, Bastos MDL, Sá SI, Capela JP, Carvalho F, Costa VM. Four decades of chemotherapy-induced cognitive dysfunction: comprehensive review of clinical, animal and in vitro studies, and insights of key initiating events. Arch Toxicol 2021; 96:11-78. [PMID: 34725718 DOI: 10.1007/s00204-021-03171-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 09/23/2021] [Indexed: 01/22/2023]
Abstract
Cognitive dysfunction has been one of the most reported and studied adverse effects of cancer treatment, but, for many years, it was overlooked by the medical community. Nevertheless, the medical and scientific communities have now recognized that the cognitive deficits caused by chemotherapy have a strong impact on the morbidity of cancer treated patients. In fact, chemotherapy-induced cognitive dysfunction or 'chemobrain' (also named also chemofog) is at present a well-recognized effect of chemotherapy that could affect up to 78% of treated patients. Nonetheless, its underlying neurotoxic mechanism is still not fully elucidated. Therefore, this work aimed to provide a comprehensive review using PubMed as a database to assess the studies published on the field and, therefore, highlight the clinical manifestations of chemobrain and the putative neurotoxicity mechanisms.In the last two decades, a great number of papers was published on the topic, mainly with clinical observations. Chemotherapy-treated patients showed that the cognitive domains most often impaired were verbal memory, psychomotor function, visual memory, visuospatial and verbal learning, memory function and attention. Chemotherapy alters the brain's metabolism, white and grey matter and functional connectivity of brain areas. Several mechanisms have been proposed to cause chemobrain but increase of proinflammatory cytokines with oxidative stress seem more relevant, not excluding the action on neurotransmission and cellular death or impaired hippocampal neurogenesis. The interplay between these mechanisms and susceptible factors makes the clinical management of chemobrain even more difficult. New studies, mainly referring to the underlying mechanisms of chemobrain and protective measures, are important in the future, as it is expected that chemobrain will have more clinical impact in the coming years, since the number of cancer survivors is steadily increasing.
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Affiliation(s)
- Ana Dias-Carvalho
- Associate Laboratory i4HB-Institute for Health and Bioeconomy, Laboratory of Toxicology, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, 4050-313, Porto, Portugal. .,UCIBIO-Applied Molecular Biosciences Unit, Laboratory of Toxicology, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, 4050-313, Porto, Portugal.
| | - Mariana Ferreira
- Associate Laboratory i4HB-Institute for Health and Bioeconomy, Laboratory of Toxicology, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, 4050-313, Porto, Portugal.,UCIBIO-Applied Molecular Biosciences Unit, Laboratory of Toxicology, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, 4050-313, Porto, Portugal.,LAQV/REQUIMTE, Department of Chemistry, University of Aveiro, Aveiro, Portugal
| | - Rita Ferreira
- LAQV/REQUIMTE, Department of Chemistry, University of Aveiro, Aveiro, Portugal
| | - Maria de Lourdes Bastos
- Associate Laboratory i4HB-Institute for Health and Bioeconomy, Laboratory of Toxicology, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, 4050-313, Porto, Portugal.,UCIBIO-Applied Molecular Biosciences Unit, Laboratory of Toxicology, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, 4050-313, Porto, Portugal
| | - Susana Isabel Sá
- Unit of Anatomy, Department of Biomedicine, Faculty of Medicine, University of Porto, Porto, Portugal.,Center for Health Technology and Services Research (CINTESIS), Faculty of Medicine, University of Porto, Porto, Portugal
| | - João Paulo Capela
- Associate Laboratory i4HB-Institute for Health and Bioeconomy, Laboratory of Toxicology, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, 4050-313, Porto, Portugal.,UCIBIO-Applied Molecular Biosciences Unit, Laboratory of Toxicology, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, 4050-313, Porto, Portugal.,Faculdade de Ciências da Saúde, Universidade Fernando Pessoa, Porto, Portugal
| | - Félix Carvalho
- Associate Laboratory i4HB-Institute for Health and Bioeconomy, Laboratory of Toxicology, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, 4050-313, Porto, Portugal.,UCIBIO-Applied Molecular Biosciences Unit, Laboratory of Toxicology, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, 4050-313, Porto, Portugal
| | - Vera Marisa Costa
- Associate Laboratory i4HB-Institute for Health and Bioeconomy, Laboratory of Toxicology, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, 4050-313, Porto, Portugal. .,UCIBIO-Applied Molecular Biosciences Unit, Laboratory of Toxicology, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, 4050-313, Porto, Portugal.
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Yung A, Kay J, Beale P, Gibson KA, Shaw T. Computer-Based Decision Tools for Shared Therapeutic Decision-making in Oncology: Systematic Review. JMIR Cancer 2021; 7:e31616. [PMID: 34544680 PMCID: PMC8579220 DOI: 10.2196/31616] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 09/13/2021] [Accepted: 09/20/2021] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Therapeutic decision-making in oncology is a complex process because physicians must consider many forms of medical data and protocols. Another challenge for physicians is to clearly communicate their decision-making process to patients to ensure informed consent. Computer-based decision tools have the potential to play a valuable role in supporting this process. OBJECTIVE This systematic review aims to investigate the extent to which computer-based decision tools have been successfully adopted in oncology consultations to improve patient-physician joint therapeutic decision-making. METHODS This review was conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 checklist and guidelines. A literature search was conducted on February 4, 2021, across the Cochrane Database of Systematic Reviews (from 2005 to January 28, 2021), the Cochrane Central Register of Controlled Trials (December 2020), MEDLINE (from 1946 to February 4, 2021), Embase (from 1947 to February 4, 2021), Web of Science (from 1900 to 2021), Scopus (from 1969 to 2021), and PubMed (from 1991 to 2021). We used a snowball approach to identify additional studies by searching the reference lists of the studies included for full-text review. Additional supplementary searches of relevant journals and gray literature websites were conducted. The reviewers screened the articles eligible for review for quality and inclusion before data extraction. RESULTS There are relatively few studies looking at the use of computer-based decision tools in oncology consultations. Of the 4431 unique articles obtained from the searches, only 10 (0.22%) satisfied the selection criteria. From the 10 selected studies, 8 computer-based decision tools were identified. Of the 10 studies, 6 (60%) were conducted in the United States. Communication and information-sharing were improved between physicians and patients. However, physicians did not change their habits to take advantage of computer-assisted decision-making tools or the information they provide. On average, the use of these computer-based decision tools added approximately 5 minutes to the total length of consultations. In addition, some physicians felt that the technology increased patients' anxiety. CONCLUSIONS Of the 10 selected studies, 6 (60%) demonstrated positive outcomes, 1 (10%) showed negative results, and 3 (30%) were neutral. Adoption of computer-based decision tools during oncology consultations continues to be low. This review shows that information-sharing and communication between physicians and patients can be improved with the assistance of technology. However, the lack of integration with electronic health records is a barrier. This review provides key requirements for enhancing the chance of success of future computer-based decision tools. However, it does not show the effects of health care policies, regulations, or business administration on physicians' propensity to adopt the technology. Nevertheless, it is important that future research address the influence of these higher-level factors as well. TRIAL REGISTRATION PROSPERO International Prospective Register of Systematic Reviews CRD42021226087; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021226087.
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Affiliation(s)
- Alan Yung
- Research in Implementation Science and eHealth, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
| | - Judy Kay
- Human Centred Technology Cluster, School of Computer Science, The University of Sydney, Sydney, Australia
| | - Philip Beale
- Concord Cancer Centre, Concord Repatriation General Hospital, Sydney, Australia
| | - Kathryn A Gibson
- Department of Rheumatology, Liverpool Hospital, Ingham Research Institute, University of New South Wales, Sydney, Australia
| | - Tim Shaw
- Research in Implementation Science and eHealth, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
- Sydney Catalyst Translational Cancer Research Centre, The University of Sydney, Sydney, Australia
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