The REAL (REctal Anastomotic Leak) score for prediction of anastomotic leak after rectal cancer surgery.
Aged
Anastomosis, Surgical
/ adverse effects
Anastomotic Leak
/ etiology
Female
Humans
Logistic Models
Male
Middle Aged
Neoplasm Staging
Nomograms
Predictive Value of Tests
Prospective Studies
Quality of Life
ROC Curve
Rectal Neoplasms
/ pathology
Rectum
/ surgery
Risk Assessment
/ methods
Risk Factors
Anastomotic leak
Rectal cancer
Score
Journal
Techniques in coloproctology
ISSN: 1128-045X
Titre abrégé: Tech Coloproctol
Pays: Italy
ID NLM: 9613614
Informations de publication
Date de publication:
Jul 2019
Jul 2019
Historique:
received:
17
01
2019
accepted:
20
06
2019
pubmed:
27
6
2019
medline:
31
3
2020
entrez:
27
6
2019
Statut:
ppublish
Résumé
Anastomotic leak after rectal cancer surgery is a severe complication associated with poorer oncologic outcome and quality of life. Preoperative assessment of the risk for anastomotic leak is a key component of surgical planning, including the opportunity to create a defunctioning stoma. The purpose of this study was to identify and quantify the risk factors for anastomotic leak to minimize risk by either not restoring bowel continuity or protecting the anastomosis with a temporary diverting stoma. Potentially relevant studies were identified from the following databases: PubMed, Embase and Cochrane Library. This meta-analysis included studies on transabdominal resection for rectal cancer that reported data about anastomotic leak. The risk for anastomotic leak after rectal cancer surgery was investigated. Preoperative, intraoperative, and postoperative factors were extracted and used to compare anastomotic leak rates. All variables demonstrating a p value < 0.1 in the univariate analysis were entered into a multivariate logistic regression model to determine the risk factors for anastomotic leak. Twenty-six centers provided individual data on 9735 patients. Selected preoperative covariates (time before surgery, age, gender, smoking, previous abdominal surgery, BMI, diabetes, ASA, hemoglobin level, TNM classification stage, anastomotic distance) were used as independent factors in a logistic regression model with anastomotic leak as dependent variable. With a threshold value of the receiver operating characteristics (ROC) curve corresponding to 0.0791 in the training set, the area under the ROC curve (AUC) was 0.585 (p < 0.0001). Sensitivity and specificity of the model's probability > 0.0791 to identify anastomotic leak were 79.1% and 32.9%, respectively. Accuracy of the threshold value was confirmed in the validation set with 77.8% sensitivity and 35.2% specificity. We trust that, with further refinement using prospective data, this nomogram based on preoperative risk factors may assist surgeons in decision making. The score is now available online ( http://www.real-score.org ).
Sections du résumé
BACKGROUND
BACKGROUND
Anastomotic leak after rectal cancer surgery is a severe complication associated with poorer oncologic outcome and quality of life. Preoperative assessment of the risk for anastomotic leak is a key component of surgical planning, including the opportunity to create a defunctioning stoma.
OBJECTIVE
OBJECTIVE
The purpose of this study was to identify and quantify the risk factors for anastomotic leak to minimize risk by either not restoring bowel continuity or protecting the anastomosis with a temporary diverting stoma.
METHODS
METHODS
Potentially relevant studies were identified from the following databases: PubMed, Embase and Cochrane Library. This meta-analysis included studies on transabdominal resection for rectal cancer that reported data about anastomotic leak. The risk for anastomotic leak after rectal cancer surgery was investigated. Preoperative, intraoperative, and postoperative factors were extracted and used to compare anastomotic leak rates. All variables demonstrating a p value < 0.1 in the univariate analysis were entered into a multivariate logistic regression model to determine the risk factors for anastomotic leak.
RESULTS
RESULTS
Twenty-six centers provided individual data on 9735 patients. Selected preoperative covariates (time before surgery, age, gender, smoking, previous abdominal surgery, BMI, diabetes, ASA, hemoglobin level, TNM classification stage, anastomotic distance) were used as independent factors in a logistic regression model with anastomotic leak as dependent variable. With a threshold value of the receiver operating characteristics (ROC) curve corresponding to 0.0791 in the training set, the area under the ROC curve (AUC) was 0.585 (p < 0.0001). Sensitivity and specificity of the model's probability > 0.0791 to identify anastomotic leak were 79.1% and 32.9%, respectively. Accuracy of the threshold value was confirmed in the validation set with 77.8% sensitivity and 35.2% specificity.
CONCLUSIONS
CONCLUSIONS
We trust that, with further refinement using prospective data, this nomogram based on preoperative risk factors may assist surgeons in decision making. The score is now available online ( http://www.real-score.org ).
Identifiants
pubmed: 31240416
doi: 10.1007/s10151-019-02028-4
pii: 10.1007/s10151-019-02028-4
doi:
Types de publication
Evaluation Study
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
649-663Investigateurs
Takashi Akiyoshi
(T)
Sergio Eduardo Alonso Araujo
(SEA)
Gian Luca Baiocchi
(GL)
Roberto Bergamaschi
(R)
Claus Anders Bertelsen
(CA)
Roberto Biffi
(R)
Marco Augusto Bonino
(MA)
Riccardo Brachet Contul
(R)
Krzysztof Bujko
(K)
Jasna But-Hadzic
(J)
Annemieke Cats
(A)
Miguel A Cuesta
(MA)
Jacopo Desiderio
(J)
Morten Tandberg Eriksen
(MT)
Serge Evrard
(S)
Dominic C C Foo
(DCC)
Hironori Fukuoka
(H)
Henrik Harling
(H)
Eiji Hidaka
(E)
Kalpesh Jani
(K)
Julien Jarry
(J)
Jin Cheon Kim
(JC)
Marilyne M Lange
(MM)
Zaher Lakkis
(Z)
Wai Lun Law
(WL)
Seok-Byung Lim
(SB)
Joseph E Martz
(JE)
Elma Meershoek-Klein Kranenbarg
(EM)
Roger Motson
(R)
Valero Navarro Graciela
(VN)
Chinnasamy Palanivelu
(C)
Yves Panis
(Y)
Amilcare Parisi
(A)
Roberto Passera
(R)
Koen C M J Peeters
(KCMJ)
Freddy Penninckx
(F)
Carlo Augusto Sartori
(CA)
Kassem Shmaissany
(K)
Matej Škrovina
(M)
Cornelis J H van de Velde
(CJH)
Vincent van der Noort
(V)
Alexander A F A Veenhof
(AAFA)
Vaneja Velenik
(V)
Arne Wibe
(A)
Karen You
(K)
Commentaires et corrections
Type : CommentIn
Type : CommentIn
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