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Health Outcome Prediction Using the Charlson Comorbidity Index In Lung Cancer Patients

Charlson Comorbidity Index를 활용한 폐암수술환자의 건강결과 예측에 관한 연구

  • Kim, Se-Won (Research Institute, Seoul Medical Center) ;
  • Yoon, Seok-Jun (Graduate School of Public Health, Korea University . Department of Preventive Medicine, College of Medicine, Korea University) ;
  • Kyung, Min-Ho (National Cancer Center) ;
  • Yun, Young-Ho (National Cancer Center) ;
  • Kim, Young-Ae (National Cancer Center,Graduate School of Public Health, Korea University) ;
  • Kim, Eun-Jung (Department of Public Health, Korea University) ;
  • Kim, Kyeong-Uoon (Department of Nursing, Khottongnae Hyundo University of Social Welfare)
  • 김세원 (서울의료원 의학연구소 정책연구실) ;
  • 윤석준 (고려대학교 보건대학원 . 고려대학교 의과대학 예방의학교실) ;
  • 경민호 (국립암센터) ;
  • 윤영호 (국립암센터) ;
  • 김영애 (국립암센터,고려대학교 보건대학원) ;
  • 김은정 (고려대학교 보건대학원 보건학협동과정) ;
  • 김경운 (꽃동네현도사회복지대학교 간호학과)
  • Published : 2009.12.30

Abstract

The goal of this study was to predict the health outcomes of lung cancer surgery based on the Charlson comorbidity index (CCI). An attempt was likewise made to assess the prognostic value of such data for predicting mortality, survival rate, and length of hospital stay. A medical-record review of 389 patients with non-small-cell lung cancer was performed. To evaluate the agreement, the kappa coefficient was tested. Logistic-regression analysis was also conducted within two years after the surgery to determine the association of CCI with death. Survival and multiple-regression analyses were used to evaluate the relationship between CCI and the hospital care outcomes within two-year survival after lung cancer surgery and the length of hospital stay. The results of the study showed that CCI is a valid prognostic indicator of two-year mortality and length of hospital stay, and that it shows the health outcomes, such as death, survival rate, and length of hospital stay, after the surgery, thus enabling the development and application of the methodology using a systematic and objective scale for the results.

Keywords

References

  1. 경민호, 윤석준, 안형식, 황세민, 서현주, 김경훈 등. 위암환자에서 의무기록과 행정자료를 활용한 Charlson Comorbidity Index의 1년 이내 사망 및 재원일수 예측력 연구. 예방의학회지 2009;42(2):117-122. https://doi.org/10.3961/jpmph.2009.42.2.117
  2. 윤석준. 건강결과 연구의 개념. 한국의료QA학회지 2007;13(1):9-12.
  3. 황세민, 윤석준, 안형식, 안형진, 김상후, 경민호 등. 위암수술환자의 건강 결과 측정을 위한 동반상병 측정도구의 유용성 연구. 예방의학회지 2009;42(1):49-58. https://doi.org/10.3961/jpmph.2009.42.1.49
  4. Baldwin LM, Klabunde CN, Green P, Barlow W, Wright G. In search of the perfect comorbidity measure for use with administrative claims data; does it exist? Med Care. 2006; 44(8):745-53. https://doi.org/10.1097/01.mlr.0000223475.70440.07
  5. Bennet A, Lacaze JC, Caron P, Berrada R, Barbe P, Louvet JP. Correlations between mean LH levels and LH pulse characteristics: differences between normal and anovulatory women, Clin Endocrinol (Oxf). 1991 Nov;35(5):431-7. https://doi.org/10.1111/j.1365-2265.1991.tb03561.x
  6. Birim O, Maat AP, Kappetein AP, van Meerbeeck JP, Damhuis RA, Bogers AJ. Validation of the Charlson comorbidity index in patients with operated primary non-small cell lung cancer. Eur J Cardiothoracic Surg. 2003;23:30-34. https://doi.org/10.1016/S1010-7940(02)00721-2
  7. Birim O, Kappetein AP, Waleboer M, Puvimanasinghe jP, Eijkemans MJ, Steyerberg EW et al. Long-term survival after non-small cell lung cancer surgery: development and validation of a prognostic model with a preoperative and postoperative mode. J Thorac Cardivasc surg. 2006 Sep;132(3):491-8. https://doi.org/10.1016/j.jtcvs.2006.04.010
  8. Beddhu S, Bruns FJ, Saul M, Seddon P, Ziedel ML. A simple comorbidity scale predicts clinical outcomes and costs in dialysis patients. Am J Med. 2000;108(8): 609-1.3 https://doi.org/10.1016/S0002-9343(00)00371-5
  9. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A New Method of Classifying Prognostic comorbidity in Longitudinal Studies: Development and Validation. J Chron Dis. 1987;40(5):373-383. https://doi.org/10.1016/0021-9681(87)90171-8
  10. Charlson M, Charlson RE, Briggs W, Hollenberg J. Can disease management target patients most likely to generate high costs? The impact of comorbidity. J Gen Intern Med. 2007 Apr;22(4):464-9. https://doi.org/10.1007/s11606-007-0130-7
  11. Deyo RA, Cherkin DC, Cioi MA. Adapting a Clinical comorbidity Index for Use with Icd-9-Cm Administrative Databases. J Clin Epidemiol. 1992;45 (6):613-619. https://doi.org/10.1016/0895-4356(92)90133-8
  12. Etienne A, Esterni B, Charbonnier A, Mozziconacci MJ, Arnoulet C, Coso D et al. comorbidity is an independent predictor of complete remission in elderly patients receiving induction chemotherapy for acute myeloid leukemia. Cancer. 2007;109(7): 1376-83. https://doi.org/10.1002/cncr.22537
  13. Extermann M. Measuring comorbidity in older cancer patients. Eur J Cancer. 2000; 36(4): 453-71. https://doi.org/10.1016/S0959-8049(99)00319-6
  14. Greenland S, Schwartzbaum JA, Finkle WD. Problems due to small samples and sparse data in conditional logistic regression analysis. Am J Epidemiol. 2000 Oct 1;152(7):688-9. https://doi.org/10.1093/aje/152.7.688
  15. Groot V, Beckerman H, Lankhorst GJ, Bouter LM. How to measure comorbidity. a critical review of available methods. J clin Epidemiol., 2003;56(3):221-9. https://doi.org/10.1016/S0895-4356(02)00585-1
  16. Guadagnoli E, silliman RA, Troyan SL, Kaplan SH, Greenfield S. The impact of age, marital status, and physician-patient interactions on the care of older women with breast carcinoma. Cancer. 1997 Oct 1;80(7):1326-34. https://doi.org/10.1002/(SICI)1097-0142(19971001)80:7<1326::AID-CNCR20>3.0.CO;2-8
  17. Iezzoni LI, Foley SM, Daley J, Hughes J, Fisher ES, Jeeren T. Comorbidities, complications, and coding bias. Boes the number of diagnosis codes matter in prediction in-hospital mortality? JAMA. 1992;267(16):2197-203. https://doi.org/10.1001/jama.267.16.2197
  18. Kane RL. Understanding health care outcomes research. 2nd ed. Jones and Bartlett publishers, 2006.
  19. Kaplan MH, Feinstein AR. The importance of classifying initial co-morbidity in evaluatin the outcome of diabetes mellitus. J Chronic Dis. 1974 Sep;27(7-8):387-404. https://doi.org/10.1016/0021-9681(74)90017-4
  20. Klabunde CN, Potosky AL, Legler JM, Warren JL. Development of a Comorbidity Index Using Physician Claims Data. J Clinical Epidemiol. 2000;53(12):1258-1267. https://doi.org/10.1016/S0895-4356(00)00256-0
  21. Klabunde CN, Warren JL, Legler JM. Assessing Comorbidity Using Claims Data: An Overview. Med Care. 2002;40(8 Suppl)Ⅳ:26-35. https://doi.org/10.1097/00005650-200201000-00005
  22. Klabunde CN, Harlan LC, Warren JL. Data Sources for Measuring Comorbidity: A Comparison of Hospital Records and Medicare Claims for Cancer Patients. Med Care. 2006;44(10):921-928. https://doi.org/10.1097/01.mlr.0000223480.52713.b9
  23. Kenny PM, King MT, Viney RC, Boyer MJ, Pollicino CA, McLean JM et al. Quality of life and survival in the 2 years after surgery for non small-cell lung cancer. J Clin Oncol. 2008 Jan 10;26(2):233-41. https://doi.org/10.1200/JCO.2006.07.7230
  24. Landis JR, Koch GG. An application of hierarchical kappa-type statistics in the assessment of majority agreement among multiple observers. Biometrics. 1977;33(2): 363-74. https://doi.org/10.2307/2529786
  25. Libero J, Peiro S, Ordinana R. Chronic comorbidity and outcomes of hodpital care: Length of stay, mortality, and readmission at 30 and 365 days. J clin Epidemiol. 1999 Mar;52(3):171-9. https://doi.org/10.1016/S0895-4356(98)00160-7
  26. Lubke T, Munig SP, Schneider PM, Hulscher AH, Bollschweiler E. Does Charlson-comorbidity index correlate with short-term outcome in patients with gastric cancer? Zentralbl Chir. 2003 Nov;128(11):970-6.(German) https://doi.org/10.1055/s-2003-44805
  27. Matsui K, Goldman L, Johnson PA, Kuntz KM, Cook EF, Lee TH. comorbidity as a correlate of length of stay for hospitalized patients with acute chest pain. J Gen Intern Med. 1996; 11(5): 262-8. https://doi.org/10.1007/BF02598265
  28. Miller MD, Paradis DF, Houck PR, Mazumdar S, Stack JA, Rifai AH, Mulsant B, Reynolds CF 3rd. Rating chronic medical illness burden in geropsychiatric practice and research: application of the Cumulative Illness Rating Scale. Psychiatry Res. 1992 Mar;41(3):237-48. https://doi.org/10.1016/0165-1781(92)90005-N
  29. Moro-sibilot D, Aubert A, Diab S, Lantuejoul S, Fourneret P, Brambilla E et al. Comorbidities and Charlson score in resected stage I nonsmall cell lung cancer. Eur Respir J. 2005; 26(3): 480-6. https://doi.org/10.1183/09031936.05.00146004
  30. Newschaffer CJ, Bush TL, Penberthy LT. Comorbidity Measurement in Elderly Female Breast Cancer Patients with Administrative and Medical Records Data. J Clin Epidemiol. 1997;50(6):725-733. https://doi.org/10.1016/S0895-4356(97)00050-4
  31. Nuttall M, van der Meulen J, Emberton M. Charlson scores based on ICD-10 administrative data were valid in assessing comorbidity in patients undergoing urological cancer surgery. J Clin Epidemiol. 2006;59(3): 265-73. https://doi.org/10.1016/j.jclinepi.2005.07.015
  32. Piccirillo JF, Spitznagel EL Jr, Vermani N, Costas I, Schnitzler M. Comparison of comorbidity indices for patients with head and neck cancer. Med Care. 2004;42(5): 482-6. https://doi.org/10.1097/01.mlr.0000124254.88292.a1
  33. Rochon PA, Katz JN, Morrow LA, McGilnchey-Berroth R, Ahlquist MM, Sarkarati M, et al. Comorbid illness is associated with survival and length of hospital stay in patients with chronic disability. A prospective comparison of three comorbidity indices. Med Care. 1996;34(11): 1093-1101. https://doi.org/10.1097/00005650-199611000-00004
  34. Shah AN, Vail TP, Taylor D, Pietrobon R. Comorbid illness affects hospital costs related to hip arthroplasty: Quantification of health status and implications for fair reimbursement and surgeon caomparison. J Arthroplasty. 2004 Sep;19(6):700-705. Truong PT, Kader HA, Lacy B, Lesperance M, MacNeil MV, Berthelet E et al. The effects of age and comorbidity on treatment and outcomes in women with endometrial cancer. Am J Clin Oncol. 2005; 28(2); 157-64. https://doi.org/10.1097/01.coc.0000143049.05090.12
  35. Wang CY, Lin YS, Tzao C, Lee HC, Huang MH, Hsu WH, Hsu HS. Comparison of Charlson comorbidity index and Kaplan-Feinstein index in patients with stage I lung cancer after surgical resection. Eur J Cardiothorac Surg. 2007 Dec;32(6):877-81. https://doi.org/10.1016/j.ejcts.2007.09.008

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