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Original Investigation |

A Novel Risk-Adjusted Nomogram for Rectal Cancer Surgery Outcomes

Maria C. Russell, MD1; Y. Nancy You, MD, MHSc2; Chung-Yuan Hu, MPH, PhD2; Janice N. Cormier, MD, MPH2; Barry W. Feig, MD2; John M. Skibber, MD2; Miguel A. Rodriguez-Bigas, MD2; Heidi Nelson, MD3; George J. Chang, MD, MS2
[+] Author Affiliations
1Department of Surgical Oncology, Emory University, Atlanta, Georgia
2Department of Surgical Oncology, University of Texas MD Anderson Cancer Center, Houston
3Department of Surgery, Mayo Clinic College of Medicine, Rochester, Minnesota
JAMA Surg. 2013;148(8):769-777. doi:10.1001/jamasurg.2013.2136.
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Importance  The circumferential resection margin is the primary determinant of local recurrence and a major factor in survival in rectal cancer. Neither chemotherapy nor chemoradiation compensates for a margin positive for cancer.

Objective  To identify treatment-related factors associated with hospital margin-positive resection and to develop a tool that could be used by individual hospitals to assess their outcomes based on their unique mix of patient and tumor characteristics.

Design  Retrospective review of the National Cancer Data Base, 1998-2007.

Settings  Community and academic/research hospitals.

Participants  Individuals with histologically confirmed localized rectal/rectosigmoid adenocarcinoma.

Exposure  All individuals underwent radical resection for rectal cancer with or without neoadjuvant therapy.

Main Outcomes and Measures  Rate of margin positivity determined and adjusted for patient- and tumor-related factors to calculate expected margin positivity per hospital. An observed to expected ratio was calculated based on patient- and tumor-related factors to identify treatment-associated variation.

Results  The overall margin-positive resection rate was 5.2%. Patients with margins positive for cancer were more likely to be older, male, and African American; not have private insurance; and have their cancer diagnosed later in the study period. Associated tumor-related factors include rectal location, higher American Joint Committee on Cancer stage, signet/mucinous histology, and poor/undifferentiated grade. Among hospitals that were significantly low outliers, 47% were comprehensive community hospitals, and 43.9% were academic/research hospitals; of those that were significantly high outliers, 52.3% were comprehensive community hospitals, and 17.8% were academic/research hospitals. High-volume centers made up 80% of significantly low outlier hospitals and 17% of significantly high outlier hospitals. The rates of chemotherapy and radiation were similar, but low outlier hospitals gave more neoadjuvant radiation (26.3% vs 17%).

Conclusions and Relevance  After adjustment for patient- and tumor-related factors, we identified both low and high outlier hospitals for margin positivity at resection, as well as potentially modifiable risk factors. The nomogram created in this model allows for the evaluation of observed and expected event rates for individual hospitals, providing a hospital self-assessment tool for identifying targets for improvement.

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Figures

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Figure 1.
Study Design

AJCC indicates American Joint Committee on Cancer, sixth edition; O/E ratio, observed to expected ratio.

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Figure 2.
Ratio of Observed to Expected Margin-Positive Rates (ie, Rates of Margins That Are Positive for Cancer)

O/E ratio indicates observed to expected ratio.

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Figure 3.
Percentage of Significantly Low and High Margin-Positive Outliers by Facility Type, Hospital Volume, and Surgery/radiation Sequence

CoC indicates Commission on Cancer of the American College of Surgeons and the American Cancer Society; O/E ratio, observed to expected ratio; Q1-Q4, 4 quartiles. The grey bars represent percentages within each category.

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Figure 4.
Nomogram for Predicting the Probability of Margin Positivity

To calculate the probability of a positive margin (ie, a margin positive for cancer), first obtain the value for each predictor by drawing a vertical line straight upward from that factor to the points’ axis, then sum the points achieved for each predictor, and locate this sum on the total points’ axis of the nomogram where the probability of a positive margin can be located by drawing a vertical line downward.

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