Patients Undergoing Resection For Oesophageal Cancer Biology Essay

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In the last two decades, P-POSSUM has been used for prediction of post operative mortality rates in general surgery based on certain clinical parameters. The speciality based O-POSSUM uses by and large the same parameters, with some modification, in predicting mortality in upper gastrointestinal surgery. These clinical parameters are available in our referral hospitals where oesophagectomy is likely to be performed. Studies to assess the efficacy of these models in oesophagectomy (1, 2, 3) have been published but literature on this in our setup is lacking. The aim of this study is to determine the accuracy of P-POSSUM and O-POSSUM in predicting the risk of 30 day mortality amongst patients undergoing resection for oesophageal cancer.

Objective: To determine the accuracy of P-POSSUM and O-POSSUM scores in predicting mortality rates in patients undergoing resection for oesophageal cancer in KNH and Nyeri PGH.

Study design: descriptive 8 month prospective study based at KNH, cardiothoracic surgery unit and Nyeri PGH.

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Materials and methods: physiological and operative details of selected patients will be taken over the period of their management. The predicted mortality will be calculated by a preset formula and compared with the actual mortality rates.

1.0 Introduction

Cancer of the oesophagus is the most common cancer amongst Kenyan males and the third most common in females (4, 5). Regional and continental studies show similar figures as those in our setup (6, 7). Resection of the oesophagus is carried out for palliative and curative purposes. Oesophageal resection carries a high mortality rate (mainly due to late presentation) of 10% (8, 9) while in specialized high volume centres mortality is reduced to 3-4% (10, 11, 12). There has been a reduction in postoperative mortality over the decades (13, 14) and this would further be reduced if those patients at higher risk were identified early and managed more aggressively. The identification of those at higher risk is the basis of using a scoring system.

Portsmouth - Physiological and Operative Severity Score for the enUmeration of Mortality and Morbidity (P-POSSUM) and Oesophagogastric POSSUM(O-POSSUM) are improvements on the original POSSUM scoring system developed by Copeland et al (15) in 1991 to assist in predicting post operative outcomes in surgical settings and also for surgical audit. They use the same 12 physiological parameters and 6 operative parameters as in POSSUM and have been used to predict 30 day mortality in patients undergoing oesophageal resection.

This study aims to evaluate the validity of these prediction tools in our local setup. Should they be valid, it would go a long way in managing these patients in the preoperative and immediate post operative period. This would translate into increasing quality of life in palliative cases which represent the majority of the cases.

2.0 Literature review

The history of POSSUM dates back to 1991 when Copeland et al designed it for post operative mortality and morbidity prediction (15). There have been various modifications which have sought to reduce the original shortcomings, mainly of over prediction (16), and also some speciality based modifications have been developed (17). The P-POSSUM model as described by Whiteley et al uses the same 12 physiological and 6 operative parameters as in the original POSSUM but uses linear regression analysis in calculation of mortality risk (18). Regionally its usefulness has been evaluated in general surgery mainly in laparatomies (19). The P-POSSUM model has been evaluated in patients undergoing resection for oesophageal cancer (1, 2). The methods used included the receiver operating characteristic (ROC) curve and the Hosmer- Lemeshow goodness of fit test. The P-POSSUM model had a moderate to good discriminatory power. There were no significant differences between predicted and observed mortality in one of the studies with a lack of fit in the other study. Testing of the model in different populations was recommended.

The O-POSSUM model was developed by Tekkis et al for upper gastrointestinal surgery. It uses 12 physiological and 3 operative variables in addition to actual age of the patient (20). This model was evaluated using the ROC and Hosmer-Lemeshow goodness of fit test (2, 3) which showed fair discriminatory power with a lack of fit on all the studies. The model tended to over predict mortality in the elderly and young. The shortcomings of the model brought up were the lack of operative data which has a bearing on the patient's survival. The authors recommend including these data especially on blood loss and testing the application in different populations. They also recommend developing a separate model for oesophageal and gastric surgery. These studies on P-POSSUM and O-POSSUM in oesophagectomy have mainly been based in Western Europe while regionally the models have been studied in general surgical cases mainly laparotomy.

3.0 Justification

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Risk prediction models have become important tools in modern day surgery as the surgical culture moves more towards outcome measures. These tools also provide the patient with as much information as possible when giving fully informed consent. Surgical audit of individual units can also be carried out using these tools and this leads to better clinical governance reviews. The models in review have been in use for the last 2 decades. Various studies carried out regionally and internationally have documented their usefulness in general and in some areas of specialized surgery (1, 2). Their use of variables which are in daily use in our setup makes it an attractive option as it would not increase costs to the patient or institutions involved.

When Earlam and Cunha-Melo reviewed oesophageal resections before the 1980's, they found it to have the highest operative mortality of any routinely performed surgery (21). Respiratory complications (28.5%) and anastomotic leaks (16.4% prevalence in our setup) are amongst some of the complications associated with this high mortality index (22, 23). Improved perioperative care (24, 25) has seen the mortality rates reduce. The use of these models would assist in identifying those areas of perioperative care that require more attention and thus would contribute to a further mortality decrease.

The ability to accurately predict mortality rates would assist medical personnel to have a more aggressive approach in the immediate post operative period to those who need it more. In our setup where intensive care is limited due to unavailability of adequate resources, this would translate in the rational allocation of these scarce resources to those who need them most (e.g. ICU beds). In palliative surgery, identification of patients at most risk would assist in the prevention of, or arresting the progression of complications. This would allow for an early discharge and less complications thus resulting in better palliation and greater savings in overall costs. In curative surgery it would help reduce post operative mortality since the surgery is not an emergency thus there would be room for correcting the physiological parameters.

Regional evaluations of these models in resection for oesophageal cancer have not been done, despite the prevalence of the problem, thus the need for this study. The different socioeconomic status in our setup might affect applicability of the score as opposed to other countries where P-POSSUM and O-POSSUM have been evaluated. Previous studies on P-POSSUM regionally were done in general surgery (19) with possible wide user variations (registrars, senior registrars) while this study will be in a specialized surgery setup. Large volume centres have been shown to have lower mortality rates (10, 11, 12) thus the choice of KNH and Nyeri PGH as the study centres.

4. Objectives

4.1 Major objective

To evaluate P-POSSUM and O-POSSUM scoring systems in the prediction of 30 day post operative mortality in patients undergoing resection for cancer of the oesophagus.

4.2 Specific objectives

To determine the number of patients undergoing resection for cancer of the oesophagus over a period of 8 months,

Identify the preoperative and intraoperative parameters as set out in the P-POSSUM and O-POSSUM scoring test,

Verify whether the predicted outcome tallies with the actual mortality rates.

5. Materials and Methods

5. 1 Study design, location and duration

Kenyatta National Hospital is the main referral centre in Kenya and is located at the heart of the capital Nairobi. Nyeri Provincial Hospital is the level 5 referral hospital in central province with an established cardiothoracic unit and the closest in proximity to the study base. The study will be based in these two institutions which routinely carry out oesophagectomies. The sample population will include all patients diagnosed with cancer of oesophagus and undergoing resection surgery over a period of 8 months. The period of data collection will be 8 month at the two cardiothoracic units.

5.2 Inclusion and Exclusion criteria

All patients confirmed to have cancer of the oesophagus and are due for elective resection surgery will be eligible for the study. Of these only those who consent will be included.

Exclusion criteria will be patients who decline to give consent and any intraoperative deaths will be also be excluded.

5.3. Data collection techniques

Data will be collected based on the P-POSSUM and O-POSSUM parameters. This will be in the form of questionnaires (appendix 1, 2) .The physiological data will be based on the latest laboratory and clinical parameters before surgery. Operative data will be collected at the end of the operative procedure. The physiological score will be calculated at induction of anaesthesia (both P-POSSUM and O-POSSUM) and operative score at the end of operation for O-POSSUM and on discharge or death of the patient for P-POSSUM.

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For standardization, all the laboratory work will be done at KNH and Nyeri PGH laboratories and preoperative and postoperative data collected by the principal investigator and research assistants who will be trained on the use of the questionnaires.

Patient follow-up will be up to postoperative day 30 and patients still on their index admission beyond 30 days will have the operative score for P-POSSUM calculated on day 30. The primary outcome will be inpatient mortality defined as death within the same admission as the operation (within a 30 day period) regardless of cause.

5.3 Data analysis

Mortality risk will be calculated using the following formula:

Log R/1-R = -9.065 + (0.1692 x physiological score) + (0.1550 x operative severity score).

where R = predicted risk of mortality

Analysis of results will be by linear analysis as described by Wijesinghe et al (26) by grouping the patients in deciles of predicted risk (appendix 3). The predicted (expected) deaths will be compared with the actual (observed) deaths, the O: E ratio. An O: E ratio above 1 indicates an under prediction while one below 1 indicates an over prediction of mortality.

The discriminatory power of the two models will be tested with the receiver operating characteristic (ROC) curve analysis and use the area under curve (AUC). A value of AUC of 1 will represent perfect discrimination, of 0.8 and above good discriminatory power, <0.8 and >0.5 represents fair discrimination while that of 0.5 and below of not better than chance.

The Hosmer Lemeshow goodness of fit test (27) will be used to assess the differences between the expected and observed mortality rates.

A value of p< 0.05 is considered to be a lack of fit. Data obtained will be managed using the Statistical Programme for Social Sciences (SPSS) version 17.0.1 statistical software.

5.4 Ethical considerations

Approval will be sought from the Kenyatta National Hospital Ethics and Research Committee before commencement of data collection. Approval will also be sought from Nyeri Provincial Hospital authorities for use of clinical data.

An informed consent shall be obtained from the patients included in the study (appendix 4).

5.6 Study limitations

Attaining an adequate sample size might be a limitation due to the late presentation of patients which precludes oesophagectomy. Of the physiological parameters, an echocardiogram might not be done for all patients and in these a baseline score of 1 will be recorded. Accuracy of intraoperative data might also present a problem.

5.7 Implementation and timetable

The study will be carried out in four phases:

Proposal writing and submission for ethical approval May 2010-October 2010

Data collection and analysis November 2010 - June 2011

Dissertation writing July 2011- Aug 2011

4. Presentation and submission of dissertation September 2011

5.8 Budget estimates

ITEM

Kshs

research fee( KNH-ERC)

1500

research assistants

25000

statistician

30000

4. stationery

15000

5. printing, typing and photocopying

25000

6. communications( airtime) + IT( hardware and software)

40000

7. contingencies/ transport

23500

TOTAL

160000

References

Lai F, Kwan TL, Yuen WC, Wai A, Siu YC , Shung E. Evaluation of various POSSUM models for predicting mortality in patients undergoing elective oesophagectomy for carcinoma, British Journal of Surgery 2007; 94: 1172-1178

Nagabhushan JS, Srinath S, Weir F, Angerson WJ, Sugden BA, Morran CG. Comparison of P-POSSUM and O-POSSUM in predicting mortality after oesophagogastric resections. Postgraduate Medical Journal 2007; 83:355-358.

Lagarde SM, Maris AKD, de Castro SMM, Busch ORC, Obertop H. Evaluation of O-POSSUM in predicting in-hospital mortality after resection for oesophageal cancer. British Journal of Surgery 2007; 94: 1521-1526

Russell EW, Christian C B, Caesar KM, Sanford MD. Oesophageal cancer: a common malignancy in young people of Bomet District, Kenya. Lancet 2002; 360: 462-63

Wakhisi J, Patel K, Buziba N, Rotich J. Esophageal cancer in North Rift Valley of western Kenya. African Health Sciences 2005; 5(2): 156-163

Mannell A, Murray W. Oesophageal cancer in South Africa, a review of 1926 cases. Cancer 1989; 64:2604-2608

Galukande M, Luwaga A, Jombwe J, Mugisa BD, Baguma P, Kigula-Mugambe JB et al. Oesophageal cancer, management guidelines for Uganda. East and Central African Journal of Surgery 2008, Vol. 13, No. 2, pp. 132-141.

Bailey SH, Bull DA, Harpole DH, Rentz JJ, Neumayer LA, Pappas TN, et al. Outcomes after oesophagectomy( ten year prospective study), Annals of Thoracic Surgery 2003;75:217-222

McCulloch P, Ward J, Tekkis PP. Mortality and morbidity in gastro-oesophageal cancer surgery: initial results of ASCOT multicentre prospective cohort study. British Medical Journal NOVEMBER 22 2003, VOLUME 327 , 1192-1197

Begg CB, Cramer LD, Hoskins WJ, Brennan MF. Impact of hospital volume on operative mortality for major cancer surgery. Journal of the American Medical Association, November 25 1998-Vol 280, No. 20, 1747-1751

Miller JD, Jain MK, de Gara CJ, Morgan D, Urschel JD. Effect of surgical experience on results of esophagectomy for esophageal carcinoma. Journal of Surgical Oncology 1997;65:20-21

Wenner J, Zilling T, Bladstrom A, Alvegard TA. The influence of surgical volume on hospital mortality and 5-year survival for carcinoma of the oesophagus and gastric cardia. Anticancer Research 2005; 25: 419-424.

Jamieson GG, Mathew G, Ludemann R, Wayman J, Myers JC , Devitt PG. Postoperative mortality following oesophagectomy and problems in reporting its rate. British Journal of Surgery 2004; 91: 943-947.

Orringer MB, Marshall B, Chang AC, Lee S, Pickens A, Lau CL. Two thousand transhiatal oesophagectomies. Changing trends, lessons learned. Annals of Surgery 2007; 246: 363-374.

Copeland GP, Jones D, Walters M. POSSUM: a scoring system for surgical audit, British Journal of Surgery, March, 1991. Vol. 78, 356-360

Whiteley MS, Prytherch DR, Higgins B, Weaver PC, Prout WG. An evaluation of the POSSUM surgical scoring system. British Journal of Surgery 1996 ,83, 812-815

Tekkis PP, Prytherch DR, Kocher HM, Senapati A, Poloniecki JD, Stamatakis JD, Windsor ACJ. Development of a dedicated risk-adjustment scoring system for colorectal surgery (colorectal POSSUM). British Journal of Surgery 2004; 91: 1174-1182.

Whiteley MS, Prytherch DR, Higgins B, Weaver PC, Prout WG, Powell SJ. POSSUM and Portsmouth POSSUM for predicting mortality. British Journal of Surgery 1998, 85, 1217-1220

Kimani MM, Kiiru JN, Matu MM, Chokwe T, Saidi H. Evaluation of POSSUM and P-POSSUM as predictors of mortality and morbidity in patients undergoing laparotomy at a referral hospital in Nairobi, Kenya., The Annals of African surgery ,January 2010 ,Volume 5 ,32-36

Tekkis PP, McCulloch P, Poloniecki JD, Prytherch DR, Kessaris N ,Steger AC. Risk-adjusted prediction of operative mortality in oesophagogastric surgery with O-POSSUM. British Journal of Surgery 2004; 91: 288-295

Earlam R, Cunha-Melo JR. Oesophageal squamous cell carcinoma I. A critical review of surgery. British Journal of Surgery. 1980 Jun; 67(6):381-90.

Atkins BZ , Shah AS, Hutcheson KA, Mangum JH, Pappas TN, Harpole DH, D'Amico TA. Reducing hospital morbidity and mortality following esophagectomy. The Annals of Thoracic Surgery, October 2004, Volume 78, Issue 4, Pages 1170-1176.

Ogendo SWO. Post oesophagectomy leakage at Kenyatta National Hospital. East and Central African Journal of Surgery,2005, Volume 10 , No. 2, pp. 77-83

Whooley BP, Law S, Murthy SC, Alexandrou A. Analysis of reduced death and complication rates after esophageal resection. Annals of Surgery,2001, Vol. 233, No. 3, 338-344

O'Rourke I, Tait N, Bull C, Gebski V, Holland M, Johnson DC. Oesophageal cancer: outcome of modern surgical management. Australia and New Zealand Journal of Surgery. 1995 Jan; 65(1):11-16.

Wijesinghe LD, Mahmood T, Scott DJA, Berridge DC, Kent PJ, Kester RC. Comparison of POSSUM and the Portsmouth predictor equation for predicting death following vascular surgery. British Journal of Surgery 1998, 85, 209-212

Hosmer D, Lemeshow S. A goodness of fit test for the mul­tiple logistic regression models. Community Statistics 1980; 10: 1043 - 1069.

APPENDIX 1

a) Physiological Score (P-POSSUM)

Score

1

2

4

8

Age (years)

<60

61-70

>71

Cardiac signs

Chest radiography

No failure

Diuretic, digoxin,

anti-angina or

hypertensive therapy

Peripheral oedema, warfarin therapy,

borderline cardiomegaly

Raised JVP,

cardiomegaly

Respiratory history

Chest radiography

No dyspnoea

Dyspnoea on

exertion

Mild COAD

Limiting dyspnoea

Moderate COAD

Dyspnoea at rest(rate>30/min)

Fibrosis or consolidation

Blood Pressure (systolic) mmHg

110-130

131-170 or

100-109

>171 or

90-99

<89

Pulse (beats/min)

50-80

81-100

40-49

101-120

>121

<39

Glasgow coma scale

15

14-12

11-9

<8

Hemoglobin (g/dl)

13-16

11.5-12.9

16.1-17.0

10.0-11.4

17.1-18.0

<9.9

>18.1

White cell count (x1012/l)

4-10

10.1-20.0

3.1-4.0

>20.1

<3.0

Urea (mmol/l)

<7.5

7.6-10.0

10.1-15.0

>15.1

Sodium (mmol/l)

>136

131-135

126-130

<125

Potassium (mmol/l)

3.5-5.0

3.2-3.4

5.1-5.3

2.9-3.1

5.4-5.9

<2.8

>6.0

Electrocardiogram

Normal

Atrial fibrillation (rate 60-90)

Any other abnormal rhythm or >5 ectopics/min

COAD - chronic obstructive airway disease

b) Operative score (P-POSSUM)

1

2

4

8

Operative severity

Minor

Moderate

Major

Complex major operation

Number of

Procedures

1

2

>2

Total blood loss(ml)

<100

101-500

501-999

>1000ml

Peritoneal soiling

None

Minor (serous fluid)

Local pus

Free bowel content, pus or blood

Presence of malignancy

none

Primary malignancy only

Malignancy +nodal metastasis

Distant metastases

Mode of surgery

Elective

Emergency resuscitation

of >2h possible <24h

after admission

Emergency (immediate surgery

<2h needed

APPENDIX 2

a) Physiological Score for O-POSSUM

Score

1

2

4

8

Age range(years)

<60

61-70

>71

Actual age

<60

61-70

>71

Cardiac signs

Chest radiography

No failure

Diuretic, digoxin,

anti-angina or

hypertensive therapy

Peripheral edema, warfarin therapy,

borderline cardiomegaly

Raised JVP,

cardiomegaly

Respiratory history

Chest radiography

No dyspnoea

Dyspnoea on

Exertion

Mild COAD

Limiting dyspnoea

Moderate COAD

Dyspnoea at rest(rate>30/min)

Fibrosis or consolidation

Blood Pressure (systolic) mmHg

110-130

131-170 or

100-109

>171 or

90-99

<89

Pulse (beats/min)

50-80

81-100

40-49

101-120

>121

<39

Glasgow coma scale

15

14-12

11-9

<8

Hemoglobin (g/dl)

13-16

11.5-12.9

16.1-17.0

10.0-11.4

17.1-18.0

<9.9

>18.1

White cell count (x1012/l)

4-10

10.1-20.0

3.1-4.0

>20.1

<3.0

Urea (mmol/l)

<7.5

7.6-10.0

10.1-15.0

>15.1

Sodium (mmol/l)

>136

131-135

126-130

<125

Potassium (mmol/l)

3.5-5.0

3.2-3.4

5.1-5.3

2.9-3.1

5.4-5.9

<2.8

>6.0

Electrocardiogram

Normal

Atrial fibrillation (rate 60-90)

Any other abnormal rhythm or >5 ectopics/min

b) Operative score (O-POSSUM)

1

2

4

8

Operative type

oesophagectomy

Total gastrectomy

Partial gastrectomy

Palliative gastrojejunostomy

Presence of malignancy

none

Primary malignancy only

Malignancy +nodal metastasis

Distant metastases

Mode of surgery

Elective

Emergency (immediate surgery

<2h needed

Appendix 3

Mortality group (%)

Number of patients

Mean risk (%)

Predicted deaths (expected)

Actual death ( observed )

O:E ratio

<10

10-29

30-39

40-49

50-59

60-69

70-79

80-89

90-100

0-100