Pre-operative Nomogram to Predict Risk of Peri-operative Mortality following Liver Resections for Malignancy

Mashaal Dhir, Lynette M Smith, Fred Ullrich, Premila D. Leiphrakpam, Quan P Ly, Aaron R. Sasson, Chandrakanth Are

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11 Citations (Scopus)

Abstract

Introduction: The majority of liver resections for malignancy are performed in older patient with major co-morbidities. There is currently no pre-operative, patient-specific method to determine the likely peri-operative mortality for each individual patient. The aim of this study was to develop a pre-operative nomogram based on the presence of co-morbidities to predict risk of peri-operative mortality following liver resections for malignancy. Methods: The Nationwide Inpatient Sample database was queried to identify adult patients that underwent liver resection for malignancy. The pre-operative co-morbidities, identified as predictors were used and a nomogram was created with multivariate regression using Taylor expansion method in SAS software, SURVEYLOGISTIC procedure. Training set (years 2000-2004) was utilized to develop the model and validation set (year 2005) was utilized to validate this model. Results: A total of 3,947 and 972 patients were included in training and validation sets, respectively. The overall actual-observed peri-operative mortality rates for training and validation sets were 4.1% and 3.2%, respectively. The decile-based calibration plots for the training set revealed good agreement between the observed probabilities and nomogram-predicted probabilities. Similarly, the quartile-based calibration plot for the validation set revealed good agreement between the observed and predicted probabilities. The accuracy of the nomogram was further reinforced by a good concordance index of 0.80 with a 95% confidence interval of 0.72 and 0.87. Conclusions: This pre-operative nomogram may be utilized to predict the risk of peri-operative mortality following liver resection for malignancy.

Original languageEnglish (US)
Pages (from-to)1770-1781
Number of pages12
JournalJournal of Gastrointestinal Surgery
Volume14
Issue number11
DOIs
StatePublished - Sep 8 2010

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Nomograms
Mortality
Liver
Neoplasms
Morbidity
Calibration
Inpatients
Software
Databases
Confidence Intervals

Keywords

  • Liver resections
  • Malignancy
  • Nomogram
  • Peri-operative mortality

ASJC Scopus subject areas

  • Surgery
  • Gastroenterology

Cite this

Pre-operative Nomogram to Predict Risk of Peri-operative Mortality following Liver Resections for Malignancy. / Dhir, Mashaal; Smith, Lynette M; Ullrich, Fred; Leiphrakpam, Premila D.; Ly, Quan P; Sasson, Aaron R.; Are, Chandrakanth.

In: Journal of Gastrointestinal Surgery, Vol. 14, No. 11, 08.09.2010, p. 1770-1781.

Research output: Contribution to journalArticle

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N2 - Introduction: The majority of liver resections for malignancy are performed in older patient with major co-morbidities. There is currently no pre-operative, patient-specific method to determine the likely peri-operative mortality for each individual patient. The aim of this study was to develop a pre-operative nomogram based on the presence of co-morbidities to predict risk of peri-operative mortality following liver resections for malignancy. Methods: The Nationwide Inpatient Sample database was queried to identify adult patients that underwent liver resection for malignancy. The pre-operative co-morbidities, identified as predictors were used and a nomogram was created with multivariate regression using Taylor expansion method in SAS software, SURVEYLOGISTIC procedure. Training set (years 2000-2004) was utilized to develop the model and validation set (year 2005) was utilized to validate this model. Results: A total of 3,947 and 972 patients were included in training and validation sets, respectively. The overall actual-observed peri-operative mortality rates for training and validation sets were 4.1% and 3.2%, respectively. The decile-based calibration plots for the training set revealed good agreement between the observed probabilities and nomogram-predicted probabilities. Similarly, the quartile-based calibration plot for the validation set revealed good agreement between the observed and predicted probabilities. The accuracy of the nomogram was further reinforced by a good concordance index of 0.80 with a 95% confidence interval of 0.72 and 0.87. Conclusions: This pre-operative nomogram may be utilized to predict the risk of peri-operative mortality following liver resection for malignancy.

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