Skip to main content
Top
Published in: Breast Cancer Research and Treatment 2/2013

01-06-2013 | Epidemiology

Comorbidity and outcomes after surgery among women with breast cancer: analysis of nationwide in-patient sample database

Authors: Ahmed Dehal, Ali Abbas, Samir Johna

Published in: Breast Cancer Research and Treatment | Issue 2/2013

Login to get access

Abstract

To examine the effect of comorbidity on risk of postoperative complications, prolonged hospitalization (defined as above median length of stay), non-routine disposition, and in-patient death among women with breast cancer after surgery. Nationwide in-patient sample is a nationwide clinical and administrative database. Discharges of patients aged 40 years and older who underwent surgery for breast cancer from 2005 to 2009 were identified. Information about patients and hospitals characteristics were obtained. Comorbidities were identified and used to calculate Charlson comorbidity index (CCI) score. We divided patients based on these scores into four groups: 0, 1, 2, and ≥3. Multivariate logistic regression analyses were used to examine risk adjusted association between CCI score and the aforementioned outcomes. We identified 70,536 patients’ discharges. Compared to a CCI score of zero as a reference group, CCI scores of 1, 2, and ≥3 increased the risk of post-operative complications by 1.7-fold, 2.6-fold, and 4.6-fold, respectively (p < 0.001). Patients with CCI scores of 1, 2, and ≥3 had higher risk of non-routine disposition by 1.3-folds, 1.7-folds, and 2.2-folds, respectively (p < 0.001). Patients with CCI scores of 1, 2, and ≥3 had higher risk of prolonged hospitalization by 1.2-folds, 1.6-folds, and 2.3-folds, respectively (p < 0.001). Similarly, CCI scores of 1, 2, and ≥3 increased risk of in-patient death by 3.1-folds (p 0.05), 5.4-folds (p 0.008), and 15.8-folds (p < 0.001), respectively. Comorbidity associated with worse in-hospital outcomes among women with breast cancer after surgery. Effective control of comorbidity in breast cancer patients may reduce post-operative morbidity and mortality.
Appendix
Available only for authorised users
Literature
1.
go back to reference Gijsen R, Hoeymans N, Schellevis FG et al (2001) Causes and consequences of comorbidity: a review. J Clin Epidemiol 54:661–674PubMedCrossRef Gijsen R, Hoeymans N, Schellevis FG et al (2001) Causes and consequences of comorbidity: a review. J Clin Epidemiol 54:661–674PubMedCrossRef
2.
go back to reference Bergman L, Dekker G, Van Kerkhoff EH et al (1991) Influence of age and comorbidity on treatment choice and survival in elderly patients with breast cancer. Breast Cancer Res Treat 18:189–198PubMedCrossRef Bergman L, Dekker G, Van Kerkhoff EH et al (1991) Influence of age and comorbidity on treatment choice and survival in elderly patients with breast cancer. Breast Cancer Res Treat 18:189–198PubMedCrossRef
3.
go back to reference Yancik R, Wesley MN, Ries LA et al (2011) Effect of age and comorbidity in postmenopausal breast cancer patients aged 55 years and older. JAMA 285:885–892CrossRef Yancik R, Wesley MN, Ries LA et al (2011) Effect of age and comorbidity in postmenopausal breast cancer patients aged 55 years and older. JAMA 285:885–892CrossRef
4.
go back to reference Greenfield S, Blanco DM, Elashoff RM et al (1987) Patterns of care related to age of breast cancer patients. JAMA 257:2766–2770PubMedCrossRef Greenfield S, Blanco DM, Elashoff RM et al (1987) Patterns of care related to age of breast cancer patients. JAMA 257:2766–2770PubMedCrossRef
5.
go back to reference Cleary PD, Greenfield S, Mulley AG et al (1991) Variations in length of stay and outcomes for six medical and surgical conditions in Massachusetts and California. JAMA 266:73–79PubMedCrossRef Cleary PD, Greenfield S, Mulley AG et al (1991) Variations in length of stay and outcomes for six medical and surgical conditions in Massachusetts and California. JAMA 266:73–79PubMedCrossRef
6.
go back to reference Deyo RA, Cherkin DC, Ciol MA (1992) Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol 45:613–619PubMedCrossRef Deyo RA, Cherkin DC, Ciol MA (1992) Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol 45:613–619PubMedCrossRef
7.
go back to reference Greenfield S, Apolone G, McNeil BJ et al (1993) The importance of co-existent disease in the occurrence of postoperative complications and one-year recovery in patients undergoing total hip replacement. Comorbidity and outcomes after hip replacement. Med Care 31:141–154PubMedCrossRef Greenfield S, Apolone G, McNeil BJ et al (1993) The importance of co-existent disease in the occurrence of postoperative complications and one-year recovery in patients undergoing total hip replacement. Comorbidity and outcomes after hip replacement. Med Care 31:141–154PubMedCrossRef
8.
go back to reference Kaplan MH, Feinstein AR (1974) The importance of classifying initial co-morbidity in evaluating the outcome of diabetes mellitus. J Chronic Dis 27:387–404PubMedCrossRef Kaplan MH, Feinstein AR (1974) The importance of classifying initial co-morbidity in evaluating the outcome of diabetes mellitus. J Chronic Dis 27:387–404PubMedCrossRef
9.
go back to reference Jencks SF, Williams DK, Kay TL (1988) Assessing hospital associated deaths from discharge data: the role of length of stay and comorbidities. JAMA 260:2240–2246PubMedCrossRef Jencks SF, Williams DK, Kay TL (1988) Assessing hospital associated deaths from discharge data: the role of length of stay and comorbidities. JAMA 260:2240–2246PubMedCrossRef
12.
go back to reference Zhang S, Ivy JS, Payton FC et al (2010) Modeling the impact of comorbidity on breast cancer patient outcomes. Health Care Manag Sci 13:137–154PubMedCrossRef Zhang S, Ivy JS, Payton FC et al (2010) Modeling the impact of comorbidity on breast cancer patient outcomes. Health Care Manag Sci 13:137–154PubMedCrossRef
13.
go back to reference Polek C, Klemm P, Hardie T et al (2004) Asian/Pacific Islander American women: age and death rates during hospitalization for breast cancer. Oncol Nurs Forum 31:69–74CrossRef Polek C, Klemm P, Hardie T et al (2004) Asian/Pacific Islander American women: age and death rates during hospitalization for breast cancer. Oncol Nurs Forum 31:69–74CrossRef
14.
go back to reference Kotwall C, Brinker C, Covington D et al (2003) Local and national trends over a decade in the surgical treatment of ductal carcinoma in situ. Am J Surg 186:723–728PubMedCrossRef Kotwall C, Brinker C, Covington D et al (2003) Local and national trends over a decade in the surgical treatment of ductal carcinoma in situ. Am J Surg 186:723–728PubMedCrossRef
15.
go back to reference Case C, Johantgen M, Steiner C (2001) Outpatient mastectomy: clinical, payer, and geographic influences. Health Serv Res 36:869–884PubMed Case C, Johantgen M, Steiner C (2001) Outpatient mastectomy: clinical, payer, and geographic influences. Health Serv Res 36:869–884PubMed
16.
go back to reference Reuben BC, Manwaring J, Neumayer LA (2009) Recent trends and predictors in immediate breast reconstruction after mastectomy in the United States. Am J Surg 198:237–243PubMedCrossRef Reuben BC, Manwaring J, Neumayer LA (2009) Recent trends and predictors in immediate breast reconstruction after mastectomy in the United States. Am J Surg 198:237–243PubMedCrossRef
17.
go back to reference Charlson ME, Pompei P, Ales KL et al (1987) A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 40:373–383PubMedCrossRef Charlson ME, Pompei P, Ales KL et al (1987) A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 40:373–383PubMedCrossRef
18.
go back to reference Quan H, Sundararajan V, Halfon P et al (2005) Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care 43:1130–1139PubMedCrossRef Quan H, Sundararajan V, Halfon P et al (2005) Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care 43:1130–1139PubMedCrossRef
19.
go back to reference Shavers VL, Harlan LC, Stevens JL (2003) Racial/ethnic variation in clinical presentation, treatment, and survival among breast cancer patients under age 35. Cancer 97:1143–1147CrossRef Shavers VL, Harlan LC, Stevens JL (2003) Racial/ethnic variation in clinical presentation, treatment, and survival among breast cancer patients under age 35. Cancer 97:1143–1147CrossRef
20.
go back to reference Dimick JB, Wainess RM, Upchurch GR et al (2005) National trends in outcomes for esophageal resection. Ann Thorac Surg 79:212–216PubMedCrossRef Dimick JB, Wainess RM, Upchurch GR et al (2005) National trends in outcomes for esophageal resection. Ann Thorac Surg 79:212–216PubMedCrossRef
21.
go back to reference Finlayson EV, Goodney PP, Birkmeyer JD (2003) Hospital volume and operative mortality in cancer surgery: a national study. Arch Surg 138:721–725PubMedCrossRef Finlayson EV, Goodney PP, Birkmeyer JD (2003) Hospital volume and operative mortality in cancer surgery: a national study. Arch Surg 138:721–725PubMedCrossRef
22.
go back to reference Guller U, Safford S, Pietrobon R et al (2005) High hospital volume is associated with better outcomes for breast cancer surgery: analysis of 233,247 Patients. World J Surg 29:994–1000PubMedCrossRef Guller U, Safford S, Pietrobon R et al (2005) High hospital volume is associated with better outcomes for breast cancer surgery: analysis of 233,247 Patients. World J Surg 29:994–1000PubMedCrossRef
23.
go back to reference Birkmeyer JD, Siewers AE, Finlayson EVA et al (2002) Hospital volume and surgical mortality in the United States. N Engl J Med 346:1128–1137PubMedCrossRef Birkmeyer JD, Siewers AE, Finlayson EVA et al (2002) Hospital volume and surgical mortality in the United States. N Engl J Med 346:1128–1137PubMedCrossRef
24.
go back to reference Gonnella JS (1996) Disease Staging, 4th edn. The MEDSTAT Group, SysteMetrics Division, Ann Arbor Gonnella JS (1996) Disease Staging, 4th edn. The MEDSTAT Group, SysteMetrics Division, Ann Arbor
25.
go back to reference Iezzoni LI, Ash AS, Shwartz M et al (1995) Predicting who dies depends on how severity is measured: implications for evaluating patient outcomes. Ann Intern Med 123:763–770PubMedCrossRef Iezzoni LI, Ash AS, Shwartz M et al (1995) Predicting who dies depends on how severity is measured: implications for evaluating patient outcomes. Ann Intern Med 123:763–770PubMedCrossRef
26.
go back to reference Houterman S, Janssen-Heijnen ML, Verheij CD et al (2004) Comorbidity has negligible impact on treatment and complications but influences survival in breast cancer patients. Br J Cancer 90:2332–2337PubMed Houterman S, Janssen-Heijnen ML, Verheij CD et al (2004) Comorbidity has negligible impact on treatment and complications but influences survival in breast cancer patients. Br J Cancer 90:2332–2337PubMed
27.
go back to reference Librero J, Peiro S, Ordnana R (1999) Chronic comorbidity and outcomes of hospital care: length of stay, mortality, and readmission at 30 and 365 days. J Clin Epidemiol 52:171–179PubMedCrossRef Librero J, Peiro S, Ordnana R (1999) Chronic comorbidity and outcomes of hospital care: length of stay, mortality, and readmission at 30 and 365 days. J Clin Epidemiol 52:171–179PubMedCrossRef
28.
go back to reference Land LH, Dalton SO, Jensen MB et al (2012) Impact of comorbidity on mortality: a cohort study of 62,591 Danish women diagnosed with early breast cancer, 1990–2008. Breast Cancer Res Treat 131:1013–1020PubMedCrossRef Land LH, Dalton SO, Jensen MB et al (2012) Impact of comorbidity on mortality: a cohort study of 62,591 Danish women diagnosed with early breast cancer, 1990–2008. Breast Cancer Res Treat 131:1013–1020PubMedCrossRef
29.
go back to reference Ahem TP, Lash TL, Thwin SS et al (2009) Impact of acquired comorbidities on all-cause mortality rates among older breast cancer survivors. Med Care 47:73–79CrossRef Ahem TP, Lash TL, Thwin SS et al (2009) Impact of acquired comorbidities on all-cause mortality rates among older breast cancer survivors. Med Care 47:73–79CrossRef
Metadata
Title
Comorbidity and outcomes after surgery among women with breast cancer: analysis of nationwide in-patient sample database
Authors
Ahmed Dehal
Ali Abbas
Samir Johna
Publication date
01-06-2013
Publisher
Springer US
Published in
Breast Cancer Research and Treatment / Issue 2/2013
Print ISSN: 0167-6806
Electronic ISSN: 1573-7217
DOI
https://doi.org/10.1007/s10549-013-2543-9

Other articles of this Issue 2/2013

Breast Cancer Research and Treatment 2/2013 Go to the issue
Webinar | 19-02-2024 | 17:30 (CET)

Keynote webinar | Spotlight on antibody–drug conjugates in cancer

Antibody–drug conjugates (ADCs) are novel agents that have shown promise across multiple tumor types. Explore the current landscape of ADCs in breast and lung cancer with our experts, and gain insights into the mechanism of action, key clinical trials data, existing challenges, and future directions.

Dr. Véronique Diéras
Prof. Fabrice Barlesi
Developed by: Springer Medicine