Effect of including cancer-specific variables on models examining short-term outcomes

Cancer

Volumn 119, Issue 7, 2013, Pages 1412-1419

  Merkow, Ryan P ^a,b,c   Kmiecik, Thomas E ^b   Bentrem, David J ^b   Winchester, David P ^a   Stewart, Andrew K ^a   Ko, Clifford Y ^a,d   Bilimoria, Karl Y ^a,b  

^a AMERICAN COLLEGE OF SURGEONS   (United States)

^b NORTHWESTERN UNIVERSITY   (United States)

^c UNIVERSITY OF COLORADO   (United States)

^d UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

American College of Surgeons National Surgical Quality Improvement Program; cancer stage; colorectal cancer; National Cancer Data Base; neoadjuvant therapy; outcomes; risk adjustment

Indexed keywords

ADULT; AGED; AMERICAN COLLEGE OF SURGEONS NATIONAL SURGERY QUALITY IMPROVEMENT PROGRAM; ARTICLE; CANCER CLASSIFICATION; CANCER MORTALITY; CANCER REGISTRY; CANCER STAGING; CANCER SURGERY; COLON RESECTION; COLORECTAL CANCER; CONFOUNDING VARIABLE; CONTROLLED STUDY; FEMALE; FUNCTIONAL ASSESSMENT; HUMAN; LAPAROSCOPIC SURGERY; MAJOR CLINICAL STUDY; MALE; MORBIDITY; NATIONAL HEALTH ORGANIZATION; OUTCOME ASSESSMENT; PRIORITY JOURNAL; RECTUM RESECTION; SURGICAL TECHNIQUE;

AGED; ANALYSIS OF VARIANCE; COLORECTAL NEOPLASMS; FEMALE; HUMANS; MALE; MIDDLE AGED; MODELS, STATISTICAL; NEOADJUVANT THERAPY; OUTCOME ASSESSMENT (HEALTH CARE); POSTOPERATIVE COMPLICATIONS; QUALITY IMPROVEMENT; REGISTRIES; RESEARCH DESIGN;

EID: 84875382775     PISSN: 0008543X     EISSN: 10970142     Source Type: Journal    
DOI: 10.1002/cncr.27891     Document Type: Article

References (36)

1. American College of Surgeons, National Surgical Quality Improvement Program. Semiannual Report, July 2011. Chicago, IL: American College of Surgeons; 2011.
2. Merkow RP, Bilimoria KY,. Currently available quality improvement initiatives in surgical oncology. Surgical oncology clinics of North America. 2012; 21: 367-375, vii.
3. Borja-Cacho D, Parsons HM, Habermann EB, Rothenberger DA, Henderson WG, Al-Refaie WB,. Assessment of ACS NSQIP's predictive ability for adverse events after major cancer surgery. Ann Surg Oncol. 2010; 17: 2274-2282.
4. Shah R, Velanovich V, Syed Z, Swartz A, Rubinfeld I,. Limitations of patient-associated co-morbidity model in predicting postoperative morbidity and mortality in pancreatic operations. J Gastrointest Surg. 2012; 16: 986-992.
5. Kansagara D, Englander H, Salanitro A, et al. Risk prediction models for hospital readmission: a systematic review. JAMA. 2011; 306: 1688-1698.
6. Mu Y, Edwards JR, Horan TC, Berrios-Torres SI, Fridkin SK,. Improving risk-adjusted measures of surgical site infection for the national healthcare safety network. Infect Control Hosp Epidemiol. 2011; 32: 970-986.
7. Moons KG, Kengne AP, Grobbee DE, et al. Risk prediction models: II. External validation, model updating, and impact assessment. Heart. 2012; 98: 691-698.
8. Spinks TE, Walters R, Feeley TW, et al. Improving cancer care through public reporting of meaningful quality measures. Health Aff (Millwood). 2011; 30: 664-672.
9. Schilling PL, Dimick JB, Birkmeyer JD,. Prioritizing quality improvement in general surgery. J Am Coll Surg. 2008; 207: 698-704.
10. Cohen ME, Bilimoria KY, Ko CY, Hall BL,. Development of an American College of Surgeons National Surgery Quality Improvement Program: morbidity and mortality risk calculator for colorectal surgery. J Am Coll Surg. 2009; 208: 1009-1016.
11. The National Quality Forum. Risk-Adjusted Colon Surgery Outcome Measure (NQF 0706). Available at: http://www.qualityforum.org/Home.aspx. Accessed October 5, 2011.
12. Raval MV, Cohen ME, Ingraham AM, et al. Improving American College of Surgeons National Surgical Quality Improvement Program risk adjustment: incorporation of a novel procedure risk score. J Am Coll Surg. 2010; 211: 715-723.
13. Khuri SF, Henderson WG, Daley J, et al. Successful implementation of the Department of Veterans Affairs' National Surgical Quality Improvement Program in the private sector: the Patient Safety in Surgery study. Ann Surg. 2008; 248: 329-336.
14. Khuri SF,. The NSQIP: a new frontier in surgery. Surgery. 2005; 138: 837-843.
15. Khuri SF,. Safety, quality, and the National Surgical Quality Improvement Program. Am Surg. 2006; 72: 994-998; discussion 1021-1030, 1133-1048.
16. Shiloach M, Frencher SK Jr, Steeger JE, et al. Toward robust information: data quality and inter-rater reliability in the American College of Surgeons National Surgical Quality Improvement Program. J Am Coll Surg. 2010; 210: 6-16.
17. Bilimoria KY, Stewart AK, Winchester DP, Ko CY,. The National Cancer Data Base: a powerful initiative to improve cancer care in the United States. Ann Surg Oncol. 2008; 15: 683-690.
18. American Medical Association. CPT 2011: Current Procedural Terminology. Chicago, IL: American Medical Association; 2011.
19. Department of Health and Human Services. The International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9 CM). Washington, DC: Government Printing Office; 1998.
20. World Health Organization. International Classification of Disease for Oncology. 3rd ed. Geneva, Switzerland: World Health Organization; 2000.
21. American College of Surgeons. National Surgical Quality Improvement Program. Chicago, IL: American College of Surgeons; 2011. Available at http://www.facs.org/acsnsqip.html. Accessed January 1, 2012.
22. Compton CC, Fritz AG, Greene FL, Trotti A, eds. AJCC Cancer Staging Manual. 7th ed. New York: Springer, 2010.
23. Commission on Cancer. Facility Oncology Registry Data Standards. Chicago, IL: Commission on Cancer; 2003-2011. Available at: http://www.facs.org/cancer/ ncdb/cocmanuals.html. Accessed April 15, 2011.
24. Hosmer DW, Lemeshow S,. Applied Logistic Regression. 2nd ed. New York: John Wiley & Sons, Inc.; 2000.
25. Koch CG, Li L, Hixson E, Tang A, Phillips S, Henderson JM,. What are the real rates of postoperative complications: elucidating inconsistencies between administrative and clinical data sources. J Am Coll Surg. 2012; 214: 798-805.
26. Steinberg SM, Popa MR, Michalek JA, Bethel MJ, Ellison EC,. Comparison of risk adjustment methodologies in surgical quality improvement. Surgery. 2008; 144: 662-667; discussion 662-667.
27. Lawson EH, Louie R, Zingmond DS, et al. A Comparison of Clinical Registry Versus Administrative Claims Data for Reporting of 30-Day Surgical Complications. Annals of surgery. 2012.
28. Bilimoria KY, Bentrem DJ, Talamonti MS, Stewart AK, Winchester DP, Ko CY,. Risk-based selective referral for cancer surgery: a potential strategy to improve perioperative outcomes. Ann Surg. 2010; 251: 708-716.
29. National Comprehensive Cancer Network (NCCN). NCCN Guidelines in Oncology: Rectal Cancer. Version 1.2012. Fort Washington, PA: NCCN; 2011. Available at: http://www.nccn.org. Accessed October 1, 2011.
30. El-Gazzaz G, Kiran RP, Lavery I,. Wound complications in rectal cancer patients undergoing primary closure of the perineal wound after abdominoperineal resection. Dis Colon Rectum. 2009; 52: 1962-1966.
31. Greenblatt DY, Rajamanickam V, Pugely AJ, Heise CP, Foley EF, Kennedy GD,. Short-term outcomes after laparoscopic-assisted proctectomy for rectal cancer: results from the ACS NSQIP. J Am Coll Surg. 2011; 212: 844-854.
32. Kapiteijn E, Marijnen CA, Nagtegaal ID, et al. Preoperative radiotherapy combined with total mesorectal excision for resectable rectal cancer. N Engl J Med. 2001; 345: 638-646.
33. Bullard KM, Trudel JL, Baxter NN, Rothenberger DA,. Primary perineal wound closure after preoperative radiotherapy and abdominoperineal resection has a high incidence of wound failure. Dis Colon Rectum. 2005; 48: 438-443.
34. Degrate L, Garancini M, Misani M, et al. Right colon, left colon, and rectal surgeries are not similar for surgical site infection development. Analysis of 277 elective and urgent colorectal resections. Int J Colorectal Dis. 2011; 26: 61-69.
35. Livingston E, Cao J, Dimick JB,. Tread carefully with stepwise regression. Arch Surg. 2010; 145: 1039-1040.
36. Merkow RP, Hall BL, Cohen ME, et al. Relevance of the c-statistic in risk-adjustment models in surgery. J Am Coll Surg. 2012; 214: 822-830.