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Interinstitutional Variation in Management Decisions for Treatment of 4 Common Types of Cancer: A Multi-institutional Cohort StudyInterinstitutional Variation in Cancer Management Decisions

Jane C. Weeks, MD, MSc; Hajime Uno, PhD; Nathan Taback, PhD; Gladys Ting, MS; Angel Cronin, MS; Thomas A. D'Amico, MD; Jonathan W. Friedberg, MD, MSc; and Deborah Schrag, MD, MPH
[+] Article and Author Information

† Deceased.


From Dana-Farber Cancer Institute, Boston, Massachusetts; University of Toronto, Toronto, Ontario; Duke University Medical Center, Durham, North Carolina; and University of Rochester Medical Center, Rochester, New York.

Grant Support: Analytic work was supported by a grant from the National Cancer Institute to the Dana-Farber Cancer Institute (RC1CA146196). The National Comprehensive Cancer Network and 18 of its member cancer centers provided funding for abstraction of medical records and curation of the cancer outcomes database.

Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M13-2231.

Reproducible Research Statement: Study protocol: Not available. Statistical code: Available from Ms Cronin (e-mail, angelm_cronin@dfci.harvard.edu). Data set: Interested investigators should contact Dr. Schrag (e-mail, deb_schrag@dfci.harvard.edu) for the requisite procedures to use the data.

Requests for Single Reprints: Deborah Schrag, MD, MPH, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215; e-mail, deb_schrag@dfci.harvard.edu.

Current Author Addresses: Drs. Uno and Schrag, Ms. Ting, and Ms. Cronin: Department of Medical Oncology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215.

Dr. Taback: Department of Statistical Sciences, University of Toronto, 6th Floor, Sidney Smith Hall, 100 St. George Street, Toronto, Ontario M5S 3G3, Canada.

Dr. D'Amico: Duke University Medical Center, Box 3496, Duke South, White Zone, Room 3589, Durham, NC 27710.

Dr. Friedberg: James P. Wilmot Cancer Center, 601 Elmwood Avenue, Box 704, Rochester, NY 14642.

Author Contributions: Conception and design: J.C. Weeks, N. Taback, G. Ting, T.A. D'Amico, J.W. Friedberg, D. Schrag.

Analysis and interpretation of the data: J.C. Weeks, N. Taback, G. Ting, A. Cronin, T.A. D'Amico, J.W. Friedberg, D. Schrag.

Drafting of the article: J.C. Weeks, H. Uno, N. Taback, G. Ting, A. Cronin, D. Schrag.

Critical revision of the article for important intellectual content: J.C. Weeks, T.A. D'Amico, J.W. Friedberg, D. Schrag.

Final approval of the article: H. Uno, N. Taback, A. Cronin, T.A. D'Amico, J.W. Friedberg, D. Schrag.

Provision of study materials or patients: J.C. Weeks, D. Schrag.

Statistical expertise: H. Uno, N. Taback, A. Cronin.

Obtaining of funding: J.C. Weeks, D. Schrag.

Administrative, technical, or logistic support: J.C. Weeks, G. Ting, D. Schrag.

Collection and assembly of data: J.C. Weeks, N. Taback, G. Ting, A. Cronin, D. Schrag.


Ann Intern Med. 2014;161(1):20-30. doi:10.7326/M13-2231
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Background: When clinical practice is governed by evidence-based guidelines and there is consensus about their validity, practice variation should be minimal. For areas in which evidence gaps exist, greater variation is expected.

Objective: To systematically assess interinstitutional variation in management decisions for 4 common types of cancer.

Design: Multi-institutional, observational cohort study of patients with cancer diagnosed between July 2006 through May 2011 and observed through 31 December 2011.

Setting: 18 cancer centers participating in the formulation of treatment guidelines and systematic outcomes assessment through the National Comprehensive Cancer Network.

Patients: 25 589 patients with incident breast cancer, colorectal cancer, lung cancer, or non-Hodgkin lymphoma.

Measurements: Interinstitutional variation for 171 binary management decisions with varying levels of supporting evidence. For each decision, variation was characterized by the median absolute deviation of the center-specific proportions.

Results: Interinstitutional variation was high (median absolute deviation >10%) for 35 of 171 (20%) oncology management decisions, including 9 of 22 (41%) decisions for non-Hodgkin lymphoma, 16 of 76 (21%) for breast cancer, 7 of 47 (15%) for lung cancer, and 3 of 26 (12%) for colorectal cancer. Forty-six percent of high-variance decisions involved imaging or diagnostic procedures and 37% involved choice of chemotherapy regimen. The evidence grade underpinning the 35 high-variance decisions was category 1 for 0%, 2A for 49%, and 2B/other for 51%.

Limitation: Physician identifiers were unavailable, and results may not generalize outside of major cancer centers.

Conclusion: The substantial variation in institutional practice manifest among cancer centers reveals a lack of consensus about optimal management for common clinical scenarios. For clinicians, awareness of management decisions with high variation should prompt attention to patient preferences. For health systems, high variation can be used to prioritize comparative effectiveness research, patient–provider education, or pathway development.

Primary Funding Source: National Cancer Institute and National Comprehensive Cancer Network.

Figures

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Figure 1.

Interinstitutional variation of binary management decisions for breast cancer.

The small dots represent the institution-specific proportions of patients receiving the less common management choice for institutions contributing at least 10 patients to the decision, and the squares represent the between-institution medians for each management decision. Decisions are ordered within National Comprehensive Cancer Network evidence grade categories by median absolute deviation from largest (on the left) to smallest (on the right). For more information on categories, see the Evidence Grading section. The numbers on the x-axis correspond to the decision number in Table 2 of the Supplement.

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Figure 2.

Interinstitutional variation of binary management decisions for colorectal cancer.

The small dots represent the institution-specific proportions of patients receiving the less common management choice for institutions contributing at least 10 patients to the decision, and the squares represent the between-institution medians for each management decision. Decisions are ordered within National Comprehensive Cancer Network evidence grade categories by median absolute deviation from largest (on the left) to smallest (on the right). For more information on categories, see the Evidence Grading section. The numbers on the x-axis correspond to the decision number in Table 3 of the Supplement.

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Figure 3.

Interinstitutional variation of binary management decisions for lung cancer.

The small dots represent the institution-specific proportions of patients receiving the less common management choice for institutions contributing at least 10 patients to the decision, and the squares represent the between-institution medians for each management decision. Decisions are ordered within National Comprehensive Cancer Network evidence grade categories by the median absolute deviation from largest (on the left) to smallest (on the right). For more information on categories, see the Evidence Grading section. The numbers on the x-axis correspond to the decision number in Table 4 of the Supplement.

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Figure 4.

Interinstitutional variation of binary management decisions for non-Hodgkin lymphoma.

The small dots represent the institution-specific proportions of patients receiving the less common management choice for institutions contributing at least 10 patients to the decision, and the squares represent the between-institution medians for each management decision. Decisions are ordered within National Comprehensive Cancer Network evidence grade categories by the median absolute deviation from largest (on the left) to smallest (on the right). For more information on categories, see the Evidence Grading section. The numbers on the x-axis correspond to the decision number in Table 5 of the Supplement.

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Figure 5.

MADs, by diseasetop), management method (middle), and evidence grade (bottom).

Circles represent MADs for unique management decisions. Squares represent the average MADs, and lines represent the corresponding 95% CIs. MAD = median absolute deviation.

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