Artificial neural network is accurate in predicting mortality in patients with cirrhosis
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perceived by each group. The purpose of this study is to compare doctor and patient perceptions of the same after hours telephone conversations. Methods: Patient-initiated, after hours telephone calls to a university based fellowship program during a 4-month period were included. Each month was covered by one of four 2nd year fellows. Information was recorded about the call. Immediately after the call, the fellow answered a 6 question survey. Within one week, the patient was called and a similar survey was administered. Only calls that had both doctor and patient surveys completed were included in this study. The surveys used a 5-point Likert scale (1-not at all, to 5-very). Ratings for points 1, 2 and 3 were combined and compared to the sum of ratings for points 4 and 5, using McNemars test. The surveys addressed the 1) Seriousness of the problem 2) Disability of the patient 3) Reasonableness of the request 4) Helpfulness of the doctor 5) Satisfaction with the recommendations and 5) Likeability of the doctor/patient. Results: There were 104 patient telephone calls assessed. Mean age of patients was 42 (range 17-85). Patients were 69% female, 83% European American, 11% African American and 6% other. Survey Question Dr. Response Pt. Response Seriousness of the problem 23% 65% * Disability of the patient 25% 53% * Reasonableness of the request 51% 97% * Helpfulness of doctor 54% 89% * Satisfaction with recommendation 72% 85% Likeability of the doctor/patient 51% 94% * *p 0.0001, p 0.01 Conclusions: Doctor and patient perceptions of after hours telephone encounters differ significantly. Compared to doctors, patients feel their problems are more severe, the interaction with the doctor is more positive and their satisfaction with suggested solutions is greater. 840 A cost-effectiveness analysis of a candidate vaccine against hepatitis E virus using the institute of medicine model Ananya Das, MD 1 * and Madhumita Sinha, MD 2 . 1 Gastroenterology, P. Singhania Research Institute, New Delhi, India; and 2 Pediatrics, Max Health Care, New Delhi, India. Purpose: Hepatitis E virus (HEV) is a major public health problem and a burden on the healthcare resources in developing countries. Phase III clinical trials of a recombinant vaccine against HEV are currently going on and the vaccine is likely to be available commercially soon. Economic analysis of such a vaccine is important so that the vaccine may ideally be priced to make it affordable in the developing countries. Methods: To evaluate various strategies of widespread vaccination of a susceptible population against HEV in developing countries from a societal perspective, a Markov model was constructed using decision analysis techniques and the Institute of Medicine vaccine model. Two different strategies of vaccination against HEV were compared with a strategy of no vaccination in a Monte Carlo simulation cohort of 10,000 healthy children living in endemic areas. Clinical and cost variables used in the analysis were obtained from published information and also derived from a series of patients with acute hepatitis due to HEV, evaluated in a metropolitan clinic in a developing country. The cost of illness was calculated using direct cost of treatment and also, indirect cost accruing from loss of workdays. The candidate vaccine was presumed to be as effective as other available vaccines with a duration of vaccine-induced immunity for at least 8 years. Discounted cost per patient and quality adjusted life years (QALY) gained in each strategy and incremental cost-effectiveness ratio were the outcome parameters. Sensitivity analyses were done with important clinical and cost variables. Results: The result of the cost-effectiveness analysis is shown in the Table. The strategy of universal vaccination dominated the other 2 strategies. The cost of the candidate vaccine critically influenced the results of the analysis; as the cost of the vaccine exceeded $ 6, the marginal cost-effectiveness of the vaccination strategies progressively increased, but even at a price three times higher than the currently available vaccines for hepatitis A and hepatitis B, the vaccination strategies were cost-effective by current stan- dards of health care intervention. Conclusions: A vaccine for universal vaccination against hepatitis E will be highly cost-effective with a marginal cost-effectiveness ratio below the currently available hepatitis vaccines. Strategy Cost Effectiveness C/E Ratio Universal $ 9.86 30.141 QALY $0.33 Screen & Vaccinate $14.82 29.384 QALY $0.50 No Vaccination $15.66 29.408 QALY $0.53 841 Artificial neural network is accurate in predicting mortality in patients with cirrhosis Ananya Das, MD 1 *, Rupa Banerjee, MD 1 , Uday C Ghoshal, MD 2 and Madhumita Sinha, MD 3 . 1 Gastroenterology, P Singhania Research Institute, New Delhi, India; 2 Gastroenterology, S Gandhi Postgraduate Institute, Lucknow, India; and 3 Pediatrics, Max Health Care, New Delhi, India. Purpose: Prediction of mortality from cirrhosis is important in planning optimal timing for evaluation for liver transplantation and also identifica- tion of high-risk patients for selective interventions. Artificial Neural Net- work (ANN) applies nonlinear statistics for pattern recognition and has been shown to be useful in predicting outcome of different diseases. We evaluated if ANN could predict 1-year mortality in patients with cirrhosis using information typically available to the clinician during initial evalu- ation. Methods: The ANN was constructed on a ANN software using clinical data from a training set of patients (n 46) selected randomly from a cohort of patients with cirrhosis who were evaluated in our institution over a 30-month period starting July 1997 (n 92). After training, the network was internally validated in the remaining patients (n 46) of the original cohort who were not selected for training and whose 1-year mortality was unknown to the ANN. The performance of ANN was compared to those of a logistic regression model constructed with the same data and also with the modified Child-Pugh’s scoring system. 1-year mortality due to cirrhosis or its complications was the outcome variable for comparing the predictive models. The neural network was also tested in an external validation sample of 62 patients admitted to another hospital in a different city. Results: The patients in the external validation sample were younger (mean age, 41 vs. 45.4 years), had less proportion of patients with alcoholic liver disease (5% vs. 49%), had less severe liver disease (mean Child’s score 6.6 vs. 10.8), and had lower 1-year mortality (13% vs. 46%). ANN had an overall accuracy of 91%, with a sensitivity and specificity of 90% and 92%, respectively in predicting 1-year mortality; area under the receiver-oper- ating curve was 0.94. The performance of the logistic regression model (overall accuracy 74%) and the Child-Pugh’s scoring system (overall accuracy 55%) was worse than the ANN (p 0.05, McNemar’s test). Despite significant differences in the statistical make-up of the internal and external validation groups, the ANN performed reasonably well in the external validation sample with a predictive accuracy of 90% and an area under the receiver-operating curve of 0.85. Conclusions: Neural network accurately predicts 1-year mortality in pa- tients with cirrhosis and may be a useful clinical instrument for risk stratification. Predictive accuracy of ANN was superior to both the Child- Pugh’s scoring system and conventional regression model and its perfor- mance did not deteriorate when tested in a different patient population. S263 AJG – September, Suppl., 2001 Abstracts
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Transcript of Artificial neural network is accurate in predicting mortality in patients with cirrhosis
perceived by each group. The purpose of this study is to compare doctorand patient perceptions of the same after hours telephone conversations.Methods: Patient-initiated, after hours telephone calls to a university basedfellowship program during a 4-month period were included. Each monthwas covered by one of four 2nd year fellows. Information was recorded aboutthe call. Immediately after the call, the fellow answered a 6 question survey.Within one week, the patient was called and a similar survey was administered.Only calls that had both doctor and patient surveys completed were includedin this study. The surveys used a 5-point Likert scale (1-not at all, to 5-very).Ratings for points 1, 2 and 3 were combined and compared to the sum ofratings for points 4 and 5, using McNemars test. The surveys addressed the 1)Seriousness of the problem 2) Disability of the patient 3) Reasonableness of therequest 4) Helpfulness of the doctor 5) Satisfaction with the recommendationsand 5) Likeability of the doctor/patient.Results: There were 104 patient telephone calls assessed. Mean age ofpatients was 42 (range 17-85). Patients were 69% female, 83% EuropeanAmerican, 11% African American and 6% other.
Survey Question Dr. Response Pt. Response
Seriousness of the problem 23% 65% *Disability of the patient 25% 53% *Reasonableness of the request 51% 97% *Helpfulness of doctor 54% 89% *Satisfaction with recommendation 72% 85%�Likeability of the doctor/patient 51% 94% *
* p � 0.0001, �p � 0.01
Conclusions: Doctor and patient perceptions of after hours telephoneencounters differ significantly. Compared to doctors, patients feel theirproblems are more severe, the interaction with the doctor is more positiveand their satisfaction with suggested solutions is greater.
840
A cost-effectiveness analysis of a candidate vaccine against hepatitisE virus using the institute of medicine modelAnanya Das, MD1* and Madhumita Sinha, MD2. 1Gastroenterology, P.Singhania Research Institute, New Delhi, India; and 2Pediatrics, MaxHealth Care, New Delhi, India.
Purpose: Hepatitis E virus (HEV) is a major public health problem and aburden on the healthcare resources in developing countries. Phase IIIclinical trials of a recombinant vaccine against HEV are currently going onand the vaccine is likely to be available commercially soon. Economicanalysis of such a vaccine is important so that the vaccine may ideally bepriced to make it affordable in the developing countries.Methods: To evaluate various strategies of widespread vaccination of asusceptible population against HEV in developing countries from a societalperspective, a Markov model was constructed using decision analysistechniques and the Institute of Medicine vaccine model. Two differentstrategies of vaccination against HEV were compared with a strategy of novaccination in a Monte Carlo simulation cohort of 10,000 healthy childrenliving in endemic areas. Clinical and cost variables used in the analysiswere obtained from published information and also derived from a series ofpatients with acute hepatitis due to HEV, evaluated in a metropolitan clinicin a developing country. The cost of illness was calculated using direct costof treatment and also, indirect cost accruing from loss of workdays. Thecandidate vaccine was presumed to be as effective as other availablevaccines with a duration of vaccine-induced immunity for at least 8 years.Discounted cost per patient and quality adjusted life years (QALY) gainedin each strategy and incremental cost-effectiveness ratio were the outcomeparameters. Sensitivity analyses were done with important clinical and costvariables.
Results: The result of the cost-effectiveness analysis is shown in the Table.The strategy of universal vaccination dominated the other 2 strategies. Thecost of the candidate vaccine critically influenced the results of the analysis;as the cost of the vaccine exceeded $ 6, the marginal cost-effectiveness ofthe vaccination strategies progressively increased, but even at a price threetimes higher than the currently available vaccines for hepatitis A andhepatitis B, the vaccination strategies were cost-effective by current stan-dards of health care intervention.Conclusions: A vaccine for universal vaccination against hepatitis E willbe highly cost-effective with a marginal cost-effectiveness ratio below thecurrently available hepatitis vaccines.
Strategy Cost Effectiveness C/E RatioUniversal $ 9.86 30.141 QALY $0.33
Screen & Vaccinate $14.82 29.384 QALY $0.50No Vaccination $15.66 29.408 QALY $0.53
841
Artificial neural network is accurate in predicting mortality inpatients with cirrhosisAnanya Das, MD1*, Rupa Banerjee, MD1, Uday C Ghoshal, MD2 andMadhumita Sinha, MD3. 1Gastroenterology, P Singhania ResearchInstitute, New Delhi, India; 2Gastroenterology, S Gandhi PostgraduateInstitute, Lucknow, India; and 3Pediatrics, Max Health Care, NewDelhi, India.
Purpose: Prediction of mortality from cirrhosis is important in planningoptimal timing for evaluation for liver transplantation and also identifica-tion of high-risk patients for selective interventions. Artificial Neural Net-work (ANN) applies nonlinear statistics for pattern recognition and hasbeen shown to be useful in predicting outcome of different diseases. Weevaluated if ANN could predict 1-year mortality in patients with cirrhosisusing information typically available to the clinician during initial evalu-ation.Methods: The ANN was constructed on a ANN software using clinicaldata from a training set of patients (n � 46) selected randomly from acohort of patients with cirrhosis who were evaluated in our institution overa 30-month period starting July 1997 (n � 92). After training, the networkwas internally validated in the remaining patients (n � 46) of the originalcohort who were not selected for training and whose 1-year mortality wasunknown to the ANN. The performance of ANN was compared to those ofa logistic regression model constructed with the same data and also with themodified Child-Pugh’s scoring system. 1-year mortality due to cirrhosis orits complications was the outcome variable for comparing the predictivemodels. The neural network was also tested in an external validationsample of 62 patients admitted to another hospital in a different city.Results: The patients in the external validation sample were younger (meanage, 41 vs. 45.4 years), had less proportion of patients with alcoholic liverdisease (5% vs. 49%), had less severe liver disease (mean Child’s score 6.6vs. 10.8), and had lower 1-year mortality (13% vs. 46%). ANN had anoverall accuracy of 91%, with a sensitivity and specificity of 90% and 92%,respectively in predicting 1-year mortality; area under the receiver-oper-ating curve was 0.94. The performance of the logistic regression model(overall accuracy 74%) and the Child-Pugh’s scoring system (overallaccuracy 55%) was worse than the ANN (p � 0.05, McNemar’s test).Despite significant differences in the statistical make-up of the internal andexternal validation groups, the ANN performed reasonably well in theexternal validation sample with a predictive accuracy of 90% and an areaunder the receiver-operating curve of 0.85.Conclusions: Neural network accurately predicts 1-year mortality in pa-tients with cirrhosis and may be a useful clinical instrument for riskstratification. Predictive accuracy of ANN was superior to both the Child-Pugh’s scoring system and conventional regression model and its perfor-mance did not deteriorate when tested in a different patient population.
S263AJG – September, Suppl., 2001 Abstracts
