Concordance between administrative claims and registry data for identifying metastasis to the bone: an exploratory analysis in prostate cancer
Open accessAbstract
BACKGROUND: To assess concordance between Medicare claims and Surveillance, Epidemiology, and End Results (SEER) reports of incident BM among prostate cancer (PCa) patients. The prevalence and consequences of bone metastases (BM) have been examined across tumor sites using healthcare claims data however the reliability of these claims-based BM measures has not been investigated. METHODS: This retrospective cohort study utilized linked registry and claims (SEER-Medicare) data on men diagnosed with incident stage IV M1 PCa between 2005 and 2007. The SEER-based measure of incident BM was cross-tabulated with three separate Medicare claims approaches to assess concordance. Sensitivity, specificity and positive predictive value (PPV) were calculated to assess the concordance between registry- and claims-based measures. RESULTS: Based on 2,708 PCa patients in SEER-Medicare, there is low to moderate concordance between the SEER- and claims-based measures of incident BM. Across the three approaches, sensitivity ranged from 0.48 (0.456 - 0.504) to 0.598 (0.574 - 0.621), specificity ranged from 0.538 (0.507 - 0.569) to 0.620 (0.590 - 0.650) and PPV ranged from 0.679 (0.651 - 0.705) to 0.690 (0.665 - 0.715). A comparison of utilization patterns between SEER-based and claims-based measures suggested avenues for improving sensitivity. CONCLUSION: Claims-based measures using BM ICD 9 coding may be insufficient to identify patients with incident BM diagnosis and should be validated against chart data to maximize their potential for population-based analyses.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
CIs and minimal clinically important differences (MCIDs) are presented to suggest plausible evidence of effect for respective study arms.
“CIs and minimal clinically important differences (MCIDs) are presented to suggest plausible evidence of effect for respective study arms.34 35”
From Mobile Health Biometrics to Enhance Exercise and Physical Activity Adherence in Type 2 Diabetes (MOTIVATE-T2D): a decentralised feasibility randomised controlled trial delivered across the UK and Canada (2025) · cites this paper as [35]
The Results (Descriptive results; page unavailable) present 95% CIs, but they are for the sensitivity, specificity, and positive predictive value of claims-based measures. The Methods (Statistical analysis; page unavailable) describe a comparison with registry data, not effects in study arms. Our copy does not report MCIDs or use CIs to suggest evidence of treatment effect. (LLM, conf=0.83)
Experimental — accuracy not yet measuredLee et al. and Bell et al. suggest using confidence intervals and the minimal clinically important difference to interpret feasibility trials.
“Lee et al35 and Bell et al34 suggest using CIs and the MCID to interpret feasibility trials.”
From Mobile Health Biometrics to Enhance Exercise and Physical Activity Adherence in Type 2 Diabetes (MOTIVATE-T2D): a decentralised feasibility randomised controlled trial delivered across the UK and Canada (2025) · cites this paper as [35]
The Results (Descriptive results; page unavailable) report confidence intervals for measures of bone-metastasis identification, not guidance on interpreting feasibility trials. The Discussion (page unavailable) addresses improving claims-based measures. Searches for feasibility trials, MCID, and Lee and Bell found no passage addressing the attributed recommendation. (LLM, conf=0.78)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Charlson, M. E., Pompei, P., Ales, K. L., & MacKenzie, C. R. (1987) · Journal of Chronic Diseases · doi:10.1016/0021-9681(87)90171-8 · Cited by 49,742 · see citing works
Beahrs, O. H., & Henson, D. E. (1992) · Medical Entomology and Zoology · Cited by 2,340 · see citing works
Pathologic fractures correlate with reduced survival in patients with malignant bone disease
Fred Saad, C., Lipton, A., Cook, R. J., Chen, Y., Smith, M. R., & Coleman, R. E. (2007) · Cancer · doi:10.1002/cncr.22991 · Cited by 664 · see citing works
Klabunde, C. N., Legler, J. M., Warren, J. L., Baldwin, L., & Schrag, D. (2007) · Annals of Epidemiology · doi:10.1016/j.annepidem.2007.03.011 · Cited by 513 · see citing works
Nørgaard, M., Jensen, A. Ø., Jacobsen, J. B., Cetin, K., Fryzek, J. P., & Sørensen, H. T. (2010) · The Journal of Urology · doi:10.1016/j.juro.2010.03.034 · Cited by 406 · see citing works
Economic burden of metastatic bone disease in the U.S.
Schulman, K. L., & Kohles, J. D. (2007) · Cancer · doi:10.1002/cncr.22678 · Cited by 241 · see citing works
Sathiakumar, N., Delzell, E., Morrisey, M. A., Falkson, C., Yong, M., Chia, V., Blackburn, J. L., Arora, T., & Kilgore, M. L. (2011) · Prostate Cancer and Prostatic Diseases · doi:10.1038/pcan.2011.7 · Cited by 219 · see citing works
DePuy, V., Anstrom, K. J., Castel, L. D., Schulman, K. A., Weinfurt, K. P., & Fred Saad, C. (2007) · Supportive Care in Cancer · doi:10.1007/s00520-006-0203-x · Cited by 145 · see citing works
The cost of treating skeletal-related events in patients with prostate cancer.
Lage, M. J., Barber, B., Harrison, D. J., et al. (2008) · PubMed · Cited by 139 · see citing works
Costs of Prostate Cancer, Metastatic to the Bone, in The Netherlands
Groot, M. T., Kruger, C. G. G. B., Pelger, R. C. M., et al. (2003) · European Urology · doi:10.1016/s0302-2838(03)00007-1 · Cited by 132 · see citing works
Sathiakumar, N., Delzell, E., Morrisey, M. A., Falkson, C. I., Yong, M., Chia, V., Blackburn, J. L., Arora, T., Brill, I. K., & Kilgore, M. L. (2011) · Breast Cancer Research and Treatment · doi:10.1007/s10549-011-1721-x · Cited by 129 · see citing works
Hassett, M. J., Ritzwoller, D. P., Taback, N., et al. (2012) · Medical Care · doi:10.1097/mlr.0b013e318277eb6f · Cited by 122 · see citing works
Barlev, A. (2010) · Journal of Managed Care Pharmacy · doi:10.18553/jmcp.2010.16.9.693 · Cited by 101 · see citing works
Delea, T. E., McKiernan, J., Brandman, J., Edelsberg, J., Sung, J., Raut, M. K., & Oster, G. (2006) · PubMed · Cited by 88 · see citing works
Identification of metastatic cancer in claims data
Nordstrom, B. L., Whyte, J. L., Stolar, M. J., Mercaldi, C. J., & Kallich, J. D. (2012) · Pharmacoepidemiology and Drug Safety · doi:10.1002/pds.3247 · Cited by 84 · see citing works
Delea, T. E., McKiernan, J., Brandman, J., et al. (2006) · Journal of Thoracic Oncology · doi:10.1016/s1556-0864(15)30361-0 · Cited by 63 · see citing works
Use of ICD‐9 coding as a proxy for stage of disease in lung cancer
Thomas, S. K., Brooks, S. E., Mullins, C. D., Baquet, C. R., & Merchant, S. (2002) · Pharmacoepidemiology and Drug Safety · doi:10.1002/pds.759 · Cited by 30 · see citing works
Self-citationVassarStats: statistical computation Web site
(2006) · Choice Reviews Online · doi:10.5860/choice.43sup-0407 · Cited by 17 · see citing works
Bruera, E. D., & Sweeney, C. (2003) · Cambridge University Press eBooks · doi:10.1017/cbo9780511550096.025 · Cited by 4 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- Bruera ED Sweeney C Bruera ED, Portenoy RK Bone pain Cancer Pain: Assessment and Management 2003 New York: Cambridge University Press 413 428
Cited by
Sorted by citations
Benitez, J., Henseler, J., Castillo, A., & Schuberth, F. (2020) · Information & Management · doi:10.1016/j.im.2019.05.003 · Cited by 1,788 · see citing works
Munn, Z., Stern, C., Aromataris, E., Lockwood, C., & Jordan, Z. (2018) · BMC Medical Research Methodology · doi:10.1186/s12874-017-0468-4 · Cited by 1,164 · see citing works
Cabitza, F., Campagner, A., Soares, F., García de Guadiana-Romualdo, L., Challa, F., Sulejmani, A., Seghezzi, M., & Carobene, A. (2021) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2021.106288 · Cited by 284 · see citing works
Reps, J. M., Schuemie, M. J., Suchard, M. A., Ryan, P. B., & Rijnbeek, P. R. (2018) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocy032 · Cited by 205 · see citing works
Stress, burnout and depression: A systematic review on DNA methylation mechanisms
Bakusic, J., Schaufeli, W., Claes, S., & Godderis, L. (2017) · Journal of Psychosomatic Research · doi:10.1016/j.jpsychores.2016.11.005 · Cited by 223 · see citing works
Nadkarni, A., Weobong, B., Weiss, H. A., McCambridge, J., Bhat, B., Katti, B., Murthy, P., King, M., McDaid, D., Park, A.-L., et al. (2017) · The Lancet · doi:10.1016/s0140-6736(16)31590-2 · Cited by 187 · see citing works
Shi, C., Goodall, M., Dumville, J., Hill, J., Norman, G., Hamer, O., Clegg, A., Watkins, C. L., Georgiou, G., Hodkinson, A., et al. (2022) · doi:10.1101/2022.02.16.22271062 · Cited by 158 · see citing works
Weng, S. F., Vaz, L., Qureshi, N., & Kai, J. (2019) · PLOS ONE · doi:10.1371/journal.pone.0214365 · Cited by 118 · see citing works
Tang, G. H., Satkunam, M., Pond, G. R., Steinberg, G. R., Blandino, G., Schünemann, H. J., & Muti, P. (2018) · Cancer Epidemiology, Biomarkers & Prevention · doi:10.1158/1055-9965.epi-17-0936 · Cited by 117 · see citing works
Rat tickling: A systematic review of applications, outcomes, and moderators.
LaFollette, M. R., O’Haire, M. E., Cloutier, S., Blankenberger, W. B., & Gaskill, B. N. (2017) · PLOS ONE · doi:10.1371/journal.pone.0175320 · Cited by 84 · see citing works
Giummarra, M. J., Cameron, P. A., Ponsford, J., Ioannou, L., Gibson, S. J., Jennings, P. A., & Georgiou-Karistianis, N. (2017) · Journal of Occupational Rehabilitation · doi:10.1007/s10926-016-9642-5 · Cited by 68 · see citing works
Blood-Based Oxidation Markers in Medicated and Unmedicated Schizophrenia Patients: A Meta-Analysis
Goh, X. X., Tang, P. Y., & Tee, S. F. (2022) · Asian Journal of Psychiatry · doi:10.1016/j.ajp.2021.102932 · Cited by 24 · see citing works
Rayburn, S. R., Coatsworth, J. D., & MacPhee, D. (2021) · Journal of Child and Family Studies · doi:10.1007/s10826-021-02105-z · Cited by 11 · see citing works
Hesketh, K., Low, J., Andrews, R., Blitz, S., Buckley, B., Falkenhain, K., Job, J., Jones, C. A., Jones, H., Jung, M. E., et al. (2025) · BMJ Open · doi:10.1136/bmjopen-2024-092260 · Cited by 9 · see citing works
Unlocking AI Chatbot Potential in Healthcare: Trust-Enhanced DeLone & McLean IS Success Model
Sarhan, M. Y., Alarify, M., & Khojah, M. (2026) · Healthcare · doi:10.3390/healthcare14101324 · Cited by 2 · see citing works
- Authors
- Onukwugha, E., Yong, C., Hussain, A., Seal, B., & Mullins, C. D.
- Affiliations
- University of Maryland, Baltimore (US)
- Bayer (United States) (US)
- Corresponding author
- Onukwugha, Eberechukwu
- Venue
- BMC Medical Research Methodology
- Published
- 2014-01-02
- Volume
- 14
- Issue
- 1
- Pages
- 1-1
- ISSN
- 1471-2288 (ISSN-L)
- PMC
- PMC3932043
- OpenAlex
- W2004345823
- Cited by
- 589
- References
- 19
- Citations by year
- 2026: 7 · 2025: 49 · 2024: 20 · 2023: 16 · 2022: 22 · 2021: 168 · 2020: 84 · 2019: 46 · 2018: 47 · 2017: 59 · 2016: 52 · 2015: 19
- FWCI
- 79.05
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMC Medical Research Methodology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- U.S. Department of Veterans Affairs
- California Department of Public Health (N01-PC-35136, 103885, N01-PC-35139, U55/CCR921930-02, N02-PC-15105)
- University of Southern California (U55/CCR921930-02, 103885, N02‐PC‐15105, N01-PC-35139, N01-PC-35136, CCR921930-02)
- Bayer HealthCare
- Centers for Disease Control and Prevention (U55/CCR921930-02)
- National Cancer Institute (N01PC35136, U55/CCR921930-02, N01PC35139, N02 PC15105)
- Topics
- Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
- Health Sciences › Medicine › Oncology › Bone health and treatments
- Health Sciences › Medicine › Oncology › Global Cancer Incidence and Screening
- Keywords
- prostate cancer, bone metastasis, Medicare claims data, SEER database, administrative claims data, data concordance, ICD-9 coding, cancer surveillance, sensitivity and specificity, positive predictive value, stage IV prostate cancer
- MeSH terms
- Aged, Aged, 80 and over, Bone Neoplasms, Delivery of Health Care, Medicare, Humans, Insurance Claim Reporting, Male, Prostatic Neoplasms, Registries, Retrospective Studies, United States, Cohort Studies, Prevalence, SEER Program
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
