|Year : 2014 | Volume
| Issue : 4 | Page : 543-548
Comparison of different scoring systems in patients undergoing colorectal cancer surgery for predicting mortality and morbidity
F Cengiz1, E Kamer2, B Zengel1, B Uyar3, C Tavusbay2, HR Unalp2
1 Department of Surgery, Izmir Bozyaka Training and Research Hospital, Izmir, Turkey
2 Izmir Katip Celebi University Ataturk Training and Research Hospital, Izmir, Turkey
3 Department of Statistics, Faculty of Science, Ege University, Izmir, Turkey
|Date of Web Publication||1-Feb-2016|
Izmir Katip Celebi University Ataturk Training and Research Hospital, Izmir
Source of Support: None, Conflict of Interest: None
Background: Preoperative risk estimation evaluating mortality and morbidity might help surgical decision. Aims: The aim of this study was to compare the sensitivities of physiologic and operative severity score for the enumeration of mortality and morbidity (POSSUM), portsmouth-POSSUM (P-POSSUM), colorectal-POSSUM (CR-POSSUM), the Association of Coloproctology of Great Britain and Ireland colorectal cancer model (ACPGBI CRC) and revised ACPGBI CRC scoring systems that are used for evaluating mortality and morbidity in colorectal surgery performed in third-level healthcare centers. Settings And Design: A retrospective analysis has been performed on 335 consecutive patients undergoing colorectal cancer surgery between 2002 and 2012. Materials And Methods: Mortality and morbidity risks of 335 patients who underwent colorectal cancer were evaluated using these scoring systems and the results were compared with actual mortality and morbidity within postoperative 30-day that extend the duration of hospital stay. Statistical Analysis Used: The receiver operating characteristic (ROC) curves were designed to identify the score values. Results: Results of POSSUM and P-POSSUM systems showed statistical differences compared with those of CR-POSSUM, ACPGBI CRC and revised ACPGBI CRC systems (P < 0.05). P-POSSUM was found to be the best scoring system for predicting mortality risk, although all scoring systems seem to be appropriate for this parameter. On the other hand POSSUM, which can predict morbidity, was found to have moderate differentiation ability due to the magnitude of the area under the ROC curve. Conclusions: Despite altering patient demographics and surgical conditions, POSSUM seems to lead as the best scoring system for predicting mortality and morbidity among others including those most-recently proposed.
Keywords: Association of Coloproctology of Great Britain and Ireland Colorectal Cancer, colorectal cancer surgery, colorectal-physiologic and operative severity score for the enumeration of mortality and morbidity, physiologic and operative severity score for the enumeration of mortality and morbidity, Portsmouth-physiologic and operative severity score for the enumeration of mortality and morbidity, revised Association of Coloproctology of Great Britain and Ireland Colorectal Cancer, surgical scoring sy
|How to cite this article:|
Cengiz F, Kamer E, Zengel B, Uyar B, Tavusbay C, Unalp H R. Comparison of different scoring systems in patients undergoing colorectal cancer surgery for predicting mortality and morbidity. Indian J Cancer 2014;51:543-8
|How to cite this URL:|
Cengiz F, Kamer E, Zengel B, Uyar B, Tavusbay C, Unalp H R. Comparison of different scoring systems in patients undergoing colorectal cancer surgery for predicting mortality and morbidity. Indian J Cancer [serial online] 2014 [cited 2020 Jan 19];51:543-8. Available from: http://www.indianjcancer.com/text.asp?2014/51/4/543/175318
| » Introduction|| |
The number and performances of healthcare centers are increased worldwide each year rendering the necessity for follow-up of the outcomes of surgical interventions. Present data do not allow accurate comparisons of surgeons and clinics since comparisons must be made among the "the comparable ones." Development of specific postoperative mortality and morbidity models for heterogenous patient populations and varying procedures in colorectal cancer surgery is problematic. Therefore, evaluations that target patients' physiological parameters and the difficulty of surgical procedure are required.
Several different predictive scoring systems have been proposed for patients undergoing surgical resection of colorectal cancer. One of the earliest, physiologic and operative severity score for the enumeration of mortality and morbidity (POSSUM) and the Association of Coloproctology of Great Britain and Ireland colorectal cancer model (ACPGBI CRC) scoring systems, which include parameters regarding patients' preoperative physiological states and the severity of surgery for predicting mortality and mortality, have been widely accepted for colorectal cancer surgery. The original model, however, consistently over predicted death in low-risk patients, leading to the portsmouth modification portsmouth-POSSUM (P-POSSUM). Recently, the colorectal disease-specific colorectal-POSSUM (CR-POSSUM) has been developed over the last years for improving the prediction of mortality of the POSSUM score system. In 2010, the online version of the ACPGBI model was revised to include age, American Society of Anesthesiology (ASA) grade, cancer stage, operative urgency, and operation type.
The aim of this study was to compare the accuracy of POSSUM, CR-POSSUM, ACPGBI CRC, revised ACPGBI CRC scoring systems, for the predictions of mortality and morbidity in patients undergoing surgical treatment for colorectal disease.
| » Materials and Methods|| |
A retrospective analysis has been performed on 335 consecutive patients undergoing colorectal cancer surgery between January 2002 and December 2012.
Preoperative patient characteristics were recorded including age, sex, mode of presentation, and ASA grade. Operative details included tumor site and operation type. The tumors were staged according to the conventional tumor, node, and metastasis system.
The risk-adjustment models were then constructed. Physiological, operative, and pathological variables were recorded according to the P-POSSUM, CR-POSSUM, ACPGBI, and ACPGBI (revised) criteria listed in [Table 1],[Table 2],[Table 3]. POSSUM contains 12 physiological (age, cardiac and respiratory history, blood pressure, heart rate, glasgow coma score, hemoglobin levels, white blood cell count, blood electrolytes, blood urea/nitrogen, latest electrocardiogram result) and six operative (severity of the surgery, number of procedures, total blood loss, peritoneal scattering, expansion of the tumor, timing of the surgery) parameters in order to predict mortality and morbidity. ACPGBI CRC scoring system containing 5 parameters (age, cancer resection status, ASA status, cancer staging, operative urgency) was developed in 2003 as an alternative to POSSUM, which did not enter routine clinical practice.
|Table 1: POSSUM, P-POSSUM and CR-POSSUM physiological (a) and operative scores (b) |
Click here to view
|Table 3: Mortality equations for calculation of risk of death by predictive score |
Click here to view
The term "morbidity" represents the conditions (leakage from an anastomosis; bleeding; infectious, renal, metabolic, thromboembolic, cardiac, respiratory or wound-related problems) which prolonged hospital stay of patients and the term "mortality" represents the death of in patients within postoperative 30-day. Postoperative follow-up forms were used for the mortality control of patients who were discharged within 30-day following surgery. Incomplete data from patients who did not pay a further visit to the hospital were completed by making phone calls.
The receiver operating characteristic (ROC) curves were designed to identify the score values for POSSUM, P-POSSUM, CR-POSSUM, ACPGBI CRC and revised ACPGBI CRC that provided the best prediction of postoperative mortality and morbidity. The level for statistical significance was set at P < 0.05 and confidence intervals were determined at the 95% level. Therefore, MedCalc for windows 5.00.017 (MedCalc Software, Mariakerke, Belgium) software was used for statistical analyses in our study.
| » Results|| |
A total of 335 patients who underwent colorectal surgery were included in our study. Male patients (n = 196) consisted 58.5% of all patients and 38.2% (n = 128) of all patients were over 70 years of age. Number of elective surgeries or curative resection was 279 (83.3%) or 265 (79.1%), respectively. Number of patients with accompanying disease was 128 (38.2%). Data regarding the clinical, pathological and operative conditions of patients have been listed in [Table 4]. Mortality and morbidity were observed in 17 and 109 patients, respectively.
[Table 1],[Table 2],[Table 3] summarize scoring parameters of the score scoring systems.
Receiver operating characteristic curve analysis revealed that POSSUM and P-POSSUM, physiologic and operative parameters of which are the same, have significantly (P < 0.05) more powerful predictive parameters from those of other scoring systems, while no statistical difference was found (P > 0.05) between predictive powers of parameters of other three scoring systems. In addition, among the parameters of POSSUM and P-POSSUM, physiologic score was found to be more predictive than operative score.
Physiologic and operative severity score for the enumeration of mortality and morbidity and P-POSSUM were also found to be significantly more predictive than ACPGBI CRC (P = 0.025 and P = 0.016, respectively) [Table 5] while there was no significant difference in terms of predicting mortality among ACPGBI CRC, revised ACPGBI CRC and CR-POSSUM, as well as among POSSUM and P-POSSUM scoring systems (P > 0.05) [Table 5] and [Table 6]. ROC Curve analysis revealed that while all scoring systems can be used, P-POSSUM is the best, for predicting the mortality rate in patients undergoing colorectal surgery.
|Table 6: Comparison of mortality rates estimated by different scoring systems |
Click here to view
Physiologic and operative severity score for the enumeration of mortality and morbidity, the only scoring system for prediction of morbidity, has been depicted in [Figure 1]. ROC Curve analysis revealed that the physiologic score was significantly (P = 0.005) more predictive than operative score in POSSUM system. Since the area under ROC curve (68.6%) is >50%, POSSUM scoring system can be used in predicting morbidity. On the other hand, the specificity of POSSUM is not great. In addition, the predictive power of POSSUM is especially low for patients younger than 70 years of age and those undergoing elective and curative surgery [Figure 1].
|Figure 1: Comparison of the parameters and morbidity estimation rates of physiologic and operative severity score for the enumeration of mortality and morbidity scoring system according to patients and varying conditions|
Click here to view
Thirty-two (45.7%) out of 70 patients who underwent palliative surgery are older than 70 years of age and 22 (31.4%) of these patients underwent urgent surgery. One hundred and sixty-nine (63.8%) out of 265 patients who underwent curative surgery were younger than 70 years of age and 231 (87.2%) of these patients underwent elective surgery. P-POSSUM was the statistically best among the score scoring systems in predicting mortality rate in patients undergoing palliative or curative surgery [Figure 2]. Elective or curative surgery was performed in 182 (87.9%) or 169 (81.6%) patients who were younger than 70 years of age (n = 207), respectively, while elective or curative surgery was performed in 97 (75.8%) or 96 (75%) patients who were older than 70 years of age (n = 128), respectively. P-POSSUM was statistically the best scoring system in predicting mortality despite the age variable [Figure 2]. P-POSSUM was statistically the best scoring system in predicting mortality in 231 (82.8%) out of 279 patients undergoing curative surgery under elective conditions, 182 (65.2%) of whom were younger than 70 years of age [Figure 2]. P-POSSUM was statistically the best scoring system in predicting mortality in 34 (60.7%) out of 56 patients undergoing curative surgery under urgent conditions, 31 (55.4%) of whom were older than 70 years of age [Figure 2].
|Figure 2: Comparison of mortality rate estimation by different scoring systems according to patients and varying conditions|
Click here to view
| » Discussion|| |
Worldwide mortality rate in colorectal surgery varies between <1% and 10.2%. The wide variation in mortality rate among countries originates from the lack of patient data standardization and heterogenicity of study groups. Thus, the 30-day mortality rate, which is accepted as the best indicator of surgical performance, does not mean more than surgery statistics of clinics and hospitals.
Physiologic and operative severity score for the enumeration of mortality and morbidity have predicted high mortality rates particularly in patients in low-risk groups as reported previously. In order to solve this problem, P-POSSUM was developed by including POSSUM the linear (regression equation constant and weight) analyses in 1996. P-POSSUM predicted the rate of mortality more accurately in our study, although with a lack of calibration, but no statistical difference from the original POSSUM, as was reported previously.,, For a better predictive value, CR-POSSUM, a specific scoring system for colorectal surgery, was developed in 2004 by reducing physiologic and operative parameters of POSSUM and using a linear equation like P-POSSUM. However, Richards et al. reported that CR-POSSUM offered no additional predictive value over P-POSSUM. We found in the present study that CR-POSSUM, which was originated from POSSUM, had different parameters which did not provide better mortality prediction than POSSUM and P-POSSUM parameters as reported in other reports in the literature.,, The lack of greater predictive value for CR-POSSUM compared with POSSUM and P-POSSUM is probably associated with the patient population evaluated and cancer type in these patients.,
In addition, although POSSUM and P-POSSUM were statistically more efficient in predicting mortality compared with ACPGBI CRC, no statistical difference was found in terms of mortality prediction between CR-POSSUM and ACPGBI CRC as well as revised ACPGBI CRC. ACPGBI CRC was revised in 2010 by increasing the number of cancer resection status parameters from 2 to 10 and renaming operative procedure. Richards et al. reported that the revised ACPGBI CRC performs better in predicting mortality for aged patients and urgent conditions. Ugolini et al. blamed the reduced number of physiologic variables included in ACPGBI CRC for lack of success in this scoring system. Although the statistical difference in predicting mortality between POSSUM/P-POSSUM and ACPGBI CRC was not observed in revised ACPGBI CRC, it did not yield a greater predictive value than ACPGBI CRC in our study. Although ACPGBI CRC and its revised version can be used in predicting mortality, they do not have statistical superiority over POSSUM and P-POSSUM scoring systems. Our findings revealed that P-POSSUM was the best scoring system in predicting mortality rate in patients undergoing colorectal surgery as reported previously.,
Despite increased rates of mortality and morbidity in high-risk cancer patients, survival rate in colorectal cancer patients is greater after curative resection than those with other types of gastrointestinal cancer. Therefore, the number of aggressive surgery and as expected, the rate of morbidity in colorectal surgery has increased. Scoring systems present objective parameters in determining the patients who require postoperative treatment, deciding the breadth of surgical procedure and declaring the surgical procedure to the patient and the accompanying person., Therefore, the up-to-dateness and ability to predict morbidity of scoring systems is of crucial importance since morbidity is more common than mortality in colorectal surgery patients; POSSUM is the only system predicting morbidity. We found in our study that POSSUM can be used for predicting morbidity since the area under ROC curve (68.6%) was >50%. However, we also think that the predictive value of POSSUM for morbidity is not excellent since 68.6% is not very high. Although POSSUM was found as predictive as P-POSSUM for mortality in our study, the reason why POSSUM was less effective in predicting morbidity can be explained by exacerbations in subclinic medical problems following anesthesia induction, which may alter postoperative expectations. Teeuwen et al. attributed the lack of success in POSSUM for predicting morbidity to improved diagnosis and treatment tools, out-of-date mathematical prediction models and increasing number of centers and surgeons performing colorectal surgery. These observations suggest that POSSUM scoring system needs another revision.
High or low rate of mortality and morbidity has been reported in several previous studies from different countries; these variations may be attributed to differences in healthcare systems, patient profiles and stages of colorectal cancer disease on diagnosis.,,, Teeuwen et al. reported that ACPGBI CRC was superior to POSSUM scoring systems with regard to mortality prediction in patients who underwent colorectal surgery with resection. However, although age, type of admission and management procedure may affect predictive power of all scoring systems, we found in our study that POSSUM and P-POSSUM provided the closest prediction to actual outcomes under different surgical conditions, as reported previously., The success of ACPGBI CRC in predicting mortality rate in colorectal surgery was attributed to the ASA and Dukes classifications included in this scoring system., Therefore, we suggest that the inclusion of ASA and Dukes classifications may improve the success of newly developed scoring systems in predicting mortality rate in colorectal surgery. However, surgical or clinical success is defined by lower morbidity and mortality than the predicted rates by scoring systems.,,
In summary, all five scoring systems investigated in the present study can be used in mortality prediction in colorectal surgery, evaluating the surgery team's performance and yielding objective data to the patient and accompanying person. However, P-POSSUM scoring system was found to be superior to all other investigated systems with regard to predicting mortality. In addition, the original POSSUM is the only system that predicts morbidity. We conclude, therefore that although recently-developed scoring systems provide valid information, POSSUM and P-POSSUM are the best scoring systems, which could be utilized as bases for future scoring system developments.
| » References|| |
Richards CH, Leitch EF, Anderson JH, McKee RF, McMillan DC, Horgan PG. The revised ACPGBI model is a simple and accurate predictor of operative mortality after potentially curative resection of colorectal cancer. Ann Surg Oncol 2011;18:3680-5.
Crea N, Di Fabio F, Pata G, Nascimbeni R. APACHE II, POSSUM, and ASA scores and the risk of perioperative complications in patients with colorectal disease. Ann Ital Chir 2009;80:177-81.
Copeland GP, Jones D, Walters M. POSSUM: A scoring system for surgical audit. Br J Surg 1991;78:355-60.
Tekkis PP, Poloniecki JD, Thompson MR, Stamatakis JD. Operative mortality in colorectal cancer: Prospective national study. BMJ 2003;327:1196-201.
Ren L, Upadhyay AM, Wang L, Li L, Lu J, Fu W. Mortality rate prediction by Physiological and Operative Severity Score for the Enumeration of Mortality and Morbidity (POSSUM), Portsmouth POSSUM and Colorectal POSSUM and the development of new scoring systems in Chinese colorectal cancer patients. Am J Surg 2009;198:31-8.
Tekkis PP, Kessaris N, Kocher HM, Poloniecki JD, Lyttle J, Windsor AC. Evaluation of POSSUM and P-POSSUM scoring systems in patients undergoing colorectal surgery. Br J Surg 2003;90:340-5.
Whiteley MS, Prytherch DR, Higgins B, Weaver PC, Prout WG. An evaluation of the POSSUM surgical scoring system. Br J Surg 1996;83:812-5.
Prytherch DR, Whiteley MS, Higgins B, Weaver PC, Prout WG, Powell SJ. POSSUM and Portsmouth POSSUM for predicting mortality. Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity. Br J Surg 1998;85:1217-20.
Can MF, Yagci G, Tufan T, Ozturk E, Zeybek N, Cetiner S. Can SAPS II predict operative mortality more accurately than POSSUM and P-POSSUM in patients with colorectal carcinoma undergoing resection? World J Surg 2008;32:589-95.
Tekkis PP, Prytherch DR, Kocher HM, Senapati A, Poloniecki JD, Stamatakis JD, et al.
Development of a dedicated risk-adjustment scoring system for colorectal surgery (colorectal POSSUM). Br J Surg 2004;91:1174-82.
Richards CH, Leitch FE, Horgan PG, McMillan DC. A systematic review of POSSUM and its related models as predictors of post-operative mortality and morbidity in patients undergoing surgery for colorectal cancer. J Gastrointest Surg 2010;14:1511-20.
Ugolini G, Rosati G, Montroni I, Zanotti S, Manaresi A, Giampaolo L, et al.
An easy-to-use solution for clinical audit in colorectal cancer surgery. Surgery 2009;145:86-92.
Vather R, Zargar-Shoshtari K, Adegbola S, Hill AG. Comparison of the possum, P-POSSUM and Cr-POSSUM scoring systems as predictors of postoperative mortality in patients undergoing major colorectal surgery. ANZ J Surg 2006;76:812-6.
Valenti V, Hernandez-Lizoain JL, Baixauli J, Pastor C, Martinez-Regueira F, Beunza JJ, et al.
Analysis of POSSUM score and postoperative morbidity in patients with rectal cancer undergoing surgery. Langenbecks Arch Surg 2009;394:55-63.
Brooks MJ, Sutton R, Sarin S. Comparison of Surgical Risk Score, POSSUM and p-POSSUM in higher-risk surgical patients. Br J Surg 2005;92:1288-92.
Horzic M, Kopljar M, Cupurdija K, Bielen DV, Vergles D, Lackovic Z. Comparison of P-POSSUM and Cr-POSSUM scores in patients undergoing colorectal cancer resection. Arch Surg 2007;142:1043-8.
Al-Homoud S, Purkayastha S, Aziz O, Smith JJ, Thompson MD, Darzi AW, et al.
Evaluating operative risk in colorectal cancer surgery: ASA and POSSUM-based predictive models. Surg Oncol 2004;13:83-92.
Teeuwen PH, Bremers AJ, Groenewoud JM, van Laarhoven CJ, Bleichrodt RP. Predictive value of POSSUM and ACPGBI scoring in mortality and morbidity of colorectal resection: A case-control study. J Gastrointest Surg 2011;15:294-303.
Senagore AJ, Warmuth AJ, Delaney CP, Tekkis PP, Fazio VW. POSSUM, p-POSSUM, and Cr-POSSUM: Implementation issues in a United States health care system for prediction of outcome for colon cancer resection. Dis Colon Rectum 2004;47:1435-41.
Bennett-Guerrero E, Hyam JA, Shaefi S, Prytherch DR, Sutton GL, Weaver PC, et al.
Comparison of P-POSSUM risk-adjusted mortality rates after surgery between patients in the USA and the UK. Br J Surg 2003;90:1593-8.
Tez M, Yoldas O, Gocmen E, Külah B, Koc M. Evaluation of P-POSSUM and CR-POSSUM scores in patients with colorectal cancer undergoing resection. World J Surg 2006;30:2266-9.
Mohil RS, Bhatnagar D, Bahadur L, Rajneesh, Dev DK, Magan M. POSSUM and P-POSSUM for risk-adjusted audit of patients undergoing emergency laparotomy. Br J Surg 2004;91:500-3.
Poon JT, Chan B, Law WL. Evaluation of P-POSSUM in surgery for obstructing colorectal cancer and correlation of the predicted mortality with different surgical options. Dis Colon Rectum 2005;48:493-8.
Ramkumar T, Ng V, Fowler L, Farouk R. A comparison of POSSUM, P-POSSUM and colorectal POSSUM for the prediction of postoperative mortality in patients undergoing colorectal resection. Dis Colon Rectum 2006;49:330-5.
Tekkis PP, Kocher HM, Bentley AJ, Cullen PT, South LM, Trotter GA, et al.
Operative mortality rates among surgeons: Comparison of POSSUM and p-POSSUM scoring systems in gastrointestinal surgery. Dis Colon Rectum 2000;43:1528-32.
Sagar PM, Hartley MN, MacFie J, Taylor BA, Copeland GP. Comparison of individual surgeon's performance. Risk-adjusted analysis with POSSUM scoring system. Dis Colon Rectum 1996;39:654-8.
[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]
|This article has been cited by|
||CR-Possum—Can It Be Used to Predict Morbidity? A Single-Centre Retrospective Study
| ||Viswakumar Prabakaran,Thamizhmathi Thangaraju,Anil C. Mathew,Vimalkumar Govindan,Vignesh Kannan,Tracy Rosalin Poulose |
| ||Indian Journal of Surgical Oncology. 2019; 10(1): 174 |
|[Pubmed] | [DOI]|