Evidence map›Paper›PMID 23222531›Full record

ArticleMedical care2014

Validating billing/encounter codes as indicators of lung, colorectal, breast, and prostate cancer recurrence using 2 large contemporary cohorts.

Michael J Hassett, Debra P Ritzwoller, Nathan Taback, Nikki Carroll, Angel M Cronin, Gladys V Ting, Deb Schrag, Joan L Warren, Mark C Hornbrook, Jane C Weeks

Open access · greenAbstract readValidation Study
In one paragraph

Article in Medical care, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 81 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
81citing papers in PubMed, 2 pooled it
3.8field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

81 citing papers in PubMed, 2 syntheses or guidelines pooled it, 116 citations in OpenAlex.

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  19. Evaluation of Algorithms Using Automated Health Plan Data to Identify Breast Cancer Recurrences.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2024
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21 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 6 institutions in 2 countries.

Michael J Hassett*Department of Medical Oncology, Center for Outcomes & Policy Research, Dana-Farber Cancer Institute †Harvard Medical School, Boston, MA ‡Institute for Health Research, Kaiser Permanente Colorado, Denver, CO §Division of Biostatistics, The University of Toronto, Toronto, ON, Canada ∥The Dana-Farber Cancer Institute, Boston, MA ¶The National Cancer Institute, Bethesda, MD #Center for Health Research, Kaiser Permanente Northwest, Portland, OR.
Debra P Ritzwoller
Nathan Taback
Nikki Carroll
Angel M Cronin
Gladys V Ting
Deb Schrag
Joan L Warren
Mark C Hornbrook
Jane C Weeks
Dana-Farber Cancer Institute · USKaiser Permanente · USHarvard University · USKaiser Permanente Center for Health Research · USNational Cancer Institute · USUniversity of Toronto · CA

Funding

The HMO Cancer Research Network (CRN)U19CA079689 · NCI · KAISER FOUNDATION HEALTH PLAN OF WASHINGTON · PI WAGNER, EDWARD H · 1999 to 2011
$62.6M
PROPENSITY SCORES IN HIERARCHICAL MODELSU01CA093344 · NCI · DANA-FARBER CANCER INSTITUTE · PI AYANIAN, JOHN Z., FOUAD, MONA N. · 2001 to 2011
$19.5M
Lung/Colon Cancer Outcomes--Cancer Research NetworkU01CA093332 · NCI · DANA-FARBER CANCER INSTITUTE · PI WEEKS, JANE C. · 2001 to 2008
$7.4M
Cancer Care Outcomes Research &Surveillance ConsortiumU01CA093324 · NCI · HARVARD UNIVERSITY (MEDICAL SCHOOL) · PI AYANIAN, JOHN Z. · 2001 to 2008
$7.1M
NC Colorectal Cancer Care Outcomes Research StudyU01CA093326 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI SANDLER, ROBERT S. · 2001 to 2008
$4.3M
Building CER Capacity: Aligning CRN, CMS, and State Resources to Map Cancer CareRC2CA148185 · NCI · DANA-FARBER CANCER INST · PI RITZWOLLER, DEBRA P, WEEKS, JANE C. · 2009 to 2009
$2.0M
Cancer Recurrence: Detection in Administrative Data, Incidence, and CostsR01CA172143 · NCI · DANA-FARBER CANCER INST · PI HASSETT, MICHAEL JAMES, RITZWOLLER, DEBRA P · 2013 to 2016
$1.7M
Comparative Effectiveness of Cancer TherapiesK05CA166208 · NCI · DANA-FARBER CANCER INST · PI WEEKS, JANE C. · 2012 to 2013
$346k
NCI NIH HHS K05 CA166208NCI NIH HHS R01 CA172143NCI NIH HHS RC2 CA148185NCI NIH HHS RC2 CA148185-01NCI NIH HHS U01 CA01013NCI NIH HHS U01 CA093324NCI NIH HHS U01 CA093326NCI NIH HHS U01 CA093332NCI NIH HHS U01 CA093344NCI NIH HHS U19 CA079689NCI NIH HHS U19 CA79689
6 · The paper itself

Abstract

backgroundA substantial proportion of cancer-related mortality is attributable to recurrent, not de novo metastatic disease, yet we know relatively little about these patients. To fill this gap, investigators often use administrative codes for secondary malignant neoplasm or chemotherapy to identify recurrent cases in population-based datasets. However, these algorithms have not been validated in large, contemporary, routine care cohorts.

objectiveTo evaluate the validity of secondary malignant neoplasm and chemotherapy codes as indicators of recurrence after definitive local therapy for stage I-III lung, colorectal, breast, and prostate cancer. RESEARCH DESIGN, SUBJECTS, AND MEASURES: We assessed the sensitivity, specificity, and positive predictive value (PPV) of these codes 14 and 60 months after diagnosis using 2 administrative datasets linked with gold-standard recurrence status information: CanCORS/Medicare (diagnoses 2003-2005) and HMO/Cancer Research Network (diagnoses 2000-2005).

resultsWe identified 929 CanCORS/Medicare patients and 5298 HMO/CRN patients. Sensitivity, specificity, and PPV ranged widely depending on which codes were included and the type of cancer. For patients with lung, colorectal, and breast cancer, the combination of secondary malignant neoplasm and chemotherapy codes was the most sensitive (75%-85%); no code-set was highly sensitive and highly specific. For prostate cancer, no code-set offered even moderate sensitivity (≤ 19%).

conclusionsSecondary malignant neoplasm and chemotherapy codes could not identify recurrent cancer without some risk of misclassification. Findings based on existing algorithms should be interpreted with caution. More work is needed to develop a valid algorithm that can be used to characterize outcomes and define patient cohorts for comparative effectiveness research studies.

Indexed as

AgedAged, 80 and overAlgorithmsBreast NeoplasmsClinical CodingCohort StudiesColorectal NeoplasmsFemaleForecastingHealth Maintenance OrganizationsHealth Status IndicatorsHumansLung NeoplasmsMaleMedicareMiddle Aged

Identifiers

PMID23222531
PMCPMC3600389
OpenAlexW2326851875

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.