Cancer Prognostic Resources: A Systematic Review and Central Repository of Webbased Cancer Prognostic Calculators
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1 Cancer Prognostic Resources: A Systematic Review and Central Repository of Webbased Cancer Prognostic Calculators 20 th Annual HMORN Conference Phoenix, AZ April 3, 2014 Presenter: Michelle Henton, MA Kaiser Permanente Colorado, Institute for Health Research Co-authors: Borsika Rabin, PhD, MPH, Bridget Gaglio, PhD, MPH, Tristan Sanders, MPH, Larissa Nekhlyudov, MD, MPH, Alfred Marcus, PhD, Sheana Bull, PhD, MPH, James W. Dearing, PhD Acknowledgements: Funding for this research was provided through the National Cancer Institute (NCI Grant # 1P20 CA )
2 Communicating cancer prognosis Patient provider communication in the cancer context involves highly complex information. Cancer prognosis is a lead topic of interest for patients, caregivers, and clinicians. Prognostic information can support multiple processes and fill various needs. Efficient communication of prognosis can be challenging. Providers use various resources and different levels of specificity when communicating about prognosis with their patients. Web-based tools have tremendous potential and increasing role in supporting patient-centered communication around various topics including cancer care.
3 Research questions What are the characteristics of currently available web-based cancer prognostic tools? AND Can these tools support patient-provider communication about cancer prognosis?
4 Cancer prognostic tool a definition Cancer prognostic tools (nomograms) are designed to support decision making including treatment decisions through providing cancer outcome predications that take diverse patient characteristics into account. Review focuses on tools that are: English version Interactive Focus on cancer Web-based Include at least one of the following measures: Cancer or non-cancer specific mortality/overall survival Disease free survival/recurrence Clinical response to treatment Progression free survival/spread Cancer therapy induced side effects
5 Methods: Review process Web search Literature search Expert input Tools identified (n=36) Tools excluded due to lack of access (n=6) Tools reviewed for eligibility (n=30) Tools excluded due to ineligibility (no focus on required outcomes) (n=8) Tools included and abstracted (n=22)
6 Methods: Variables of interest Variables of interest: 1. General characteristics and purpose Goal, cancer sites, intended user, disclaimer, etc. 2. Data Algorithm, validation, data source, etc. 3. Input factors Demographics, cancer characteristics, comorbidities, etc. 4. Output measures Survival measures, quality of life, spread, etc. 5. Display of data Visual display, output content and format, etc. 6. Usability Print/save function, missing data, FAQ, etc. 7. Patient-centeredness Health literacy/numeracy, interpretation, connection to EHR, etc. 8. Other specifications Access, cost, accessibility, etc.
7 Cancer Prognostic Tools Tool Name Brief Name Developer Adjuvant Online Adjuvant Adjuvant! Inc. AJCC Individualized Melanoma Patient Outcome Prediction Tools AJCC American Joint Committee on Cancer Artificial Neural Networks in Prostate Cancer ANN Institute for Dynamic Educational Advancement Biochemical Recurrence-free Survival Prediction Model BioChemical Duke Prostate Center CancerMath UCSF Capra Score Cancer Survival Query System Disease free survival calculator for EBRT, brachytherapy and combinations of the two FinProg Online Nomograms for predictiong survival of GBM patients CancerMath Capra CSQS EBRT FinProg GBM CancerMath.net University of California San Francisco Medical Center National Cancer Institute Professor Les Bradbury The FinProg Research Group European Organisation for Research and Treatment of Cancer
8 Tool Name Brief Name Developer IBTR Breast Cancer Module Version 2.0 IBTR Unknown Knight Cancer Institute Survival Prediction Tools Lerner Research Institute Risk Calculators KCI Lerner Knight Cancer Institute at Oregon Health and Science University Cleveland Clinic - Lerner Research Institute MAASTRO prediction website MD Anderson Clinical calculators Memorial Sloan-Kettering Prediction Tools University of Montreal - Nomograms MAASTRO MD Anderson MSK Nomograms MAASTRO Clinic MD Anderson Cancer Center Memorial Sloan Kettering Cancer Center University of Montreal Mayo Clinic Adjuvant Tool (Numeracy) Numeracy Mayo Clinic Prognostigram QxMD Calculate Calculator for Estimating Overall Life Expectancy and Lifetime Risk for Prostate Cancer Death in Newly Diagnosed Men Managed without Definitive Local Therapy Prognostigram QxMD Roswell Park Washington University in St. Louis QxMD Roswell Park Cancer Institute
9 Findings: General characteristics and purpose At the time of the review (2012), a total of 22 tools reviewed and abstracted with 107 stand alone calculators and 89 unique cancer sites More tools have been added to the site Great variation in the number of calculators (min: 1; max: 22) the number of cancer sites (min: 1; max: 84) Top five cancer sites: Prostate (n=11) Colorectal (n=10) Breast (n=8) Genitourinary cancers (n=6) Melanoma (n=6)
10 Findings: General characteristics and purpose Purpose: Baseline prognostic information Support treatment decision after diagnosis Decide on benefits for adjuvant therapy Cancer stage: Various limitations (e.g., no metastasis, certain stage) Intended user: Most for cancer specialists/physicians Only 4 tools mentions patients as potential users
11 Findings: Data Data source: Population-based Clinic-based Mixed All except one reported validation of algorithm for at least one calculator Reporting of algorithms used by tools was variable
12 Findings: Input factors Input domain Example # of tools included Cancer characteristics Tumor size, nodal status, grade Demographic characteristics Age, gender, marital status Co-morbidities Specific/generic 9 Therapy impact Chemo, Radiation 19 Genetic characteristics ER/PR, HER2, HBOC syndrome 5 Modifiable risk factors Smoking status 2
13 Findings: Output measures Measure # of tools included Cancer specific mortality/survival 17 Disease/Progression free survival 16 Non-cancer specific survival 4 Clinical response to treatment 2 Therapy-induced side effects 2
14 Findings: Usability Function # of tools included Print/Save/ 6 FAQ for user guide 8 Documentation 5 Technical assistance 9 Time to use Average > 1 min
15 Systematic review of cancer prognostic tools Rabin BA, Gaglio B, Sanders T, Nekhlyudov L, Dearing JW, Bull S, Glasgow RE, Marcus A. Predicting cancer prognosis using interactive online tools: A systematic review and implications for cancer care providers. Cancer Epidemiology, Biomarkers, & Prevention, 2013:22:1625
16 Cancer Prognostic Resources Website
17 Cancer Prognostic Resources Website: View All Tools
18 Cancer Prognostic Resources Website: Compare Tools by Cancer Site
19 Cancer Prognostic Resources Website: Search Tools
20 Cancer Prognostic Resources Website: Individual Tool Details
21 Cancer Prognostic Resources Website: Submit a Tool
22 Cancer Prognostic Resources Website Website: Facebook: facebook.com/cancercalculators Twitter: twitter.com/cancercalc
23
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