J Gastric Cancer.  2015 Dec;15(4):262-269. 10.5230/jgc.2015.15.4.262.

Nomogram Estimating the Probability of Intraabdominal Abscesses after Gastrectomy in Patients with Gastric Cancer

Affiliations
  • 1Gastric Cancer Branch, Research Institute and Hospital, National Cancer Center, Goyang, Korea. gskim@ncc.re.kr
  • 2Biometric Research Branch, Research Institute and Hospital, National Cancer Center, Goyang, Korea.

Abstract

PURPOSE
Intraabdominal abscess is one of the most common reasons for re-hospitalization after gastrectomy. This study aimed to develop a model for estimating the probability of intraabdominal abscesses that can be used during the postoperative period.
MATERIALS AND METHODS
We retrospectively reviewed the clinicopathological data of 1,564 patients who underwent gastrectomy for gastric cancer between 2010 and 2012. Twenty-six related markers were analyzed, and multivariate logistic regression analysis was used to develop the probability estimation model for intraabdominal abscess. Internal validation using a bootstrap approach was employed to correct for bias, and the model was then validated using an independent dataset comprising of patients who underwent gastrectomy between January 2008 and March 2010. Discrimination and calibration abilities were checked in both datasets.
RESULTS
The incidence of intraabdominal abscess in the development set was 7.80% (122/1,564). The surgical approach, operating time, pathologic N classification, body temperature, white blood cell count, C-reactive protein level, glucose level, and change in the hemoglobin level were significant predictors of intraabdominal abscess in the multivariate analysis. The probability estimation model that was developed on the basis of these results showed good discrimination and calibration abilities (concordance index=0.828, Hosmer-Lemeshow chi-statistic P=0.274). Finally, we combined both datasets to produce a nomogram that estimates the probability of intraabdominal abscess.
CONCLUSIONS
This nomogram can be useful for identifying patients at a high risk of intraabdominal abscess. Patients at a high risk may benefit from further evaluation or treatment before discharge.

Keyword

Stomach neoplasms; Postoperative complications; Abdominal abscess; Nomograms

MeSH Terms

Abdominal Abscess
Abscess*
Bias (Epidemiology)
Body Temperature
C-Reactive Protein
Calibration
Classification
Dataset
Discrimination (Psychology)
Gastrectomy*
Glucose
Humans
Incidence
Leukocyte Count
Logistic Models
Multivariate Analysis
Nomograms*
Postoperative Complications
Postoperative Period
Retrospective Studies
Stomach Neoplasms*
C-Reactive Protein
Glucose

Figure

  • Fig. 1 Receiever-operator characteristic curve and calibration plots of the prediction model for the development dataset and the entire (development and validation) dataset. AUC = area under the receiver operating characteristics curve; CI = confidence interval.

  • Fig. 2 A nomogram estimating the probability of developing intraabdominal abscess after gastrectomy. OP = operative; WBC = white blood cell; CRP = C-reactive protein; Hb = hemoglobin.


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