C‐reactive protein (CRP) trajectory as a predictor of anastomotic leakage after rectal cancer resection: A multicentre cohort study

Hoek, Vincent T.; Sparreboom, Cloë L; Wolthuis, Albert; Menon, Anand; Kleinrensink, Gert-Jan; D’Hoore, André; Komen, Niels; Lange, Johan F.

doi:10.1111/codi.15963

Cited by 5 publications

(3 citation statements)

References 22 publications

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“…Additionally, we found that variational index also contributed greatly in the model (Figure 4 ), like minimum albumin level, maximum count of white blood cell and maximum ascending amount of CRP etc. Several studies have learnt the importance of trajectory of clinical variables in prognostic research 33 , 34 , although some of the research also suggested that variational index alone lacked predictive value to rule out postoperative AL 35 . In this study, we combined variational index with other perioperative variables and examined by machine learning methods, and eventually found the clinical contribution and importance of the changes in these variables.…”

Section: Discussionmentioning

confidence: 99%

Machine Learning-based Correlation Study between Perioperative Immunonutritional Index and Postoperative Anastomotic Leakage in Patients with Gastric Cancer

Liu¹,

Su²,

Qi³

et al. 2022

Int. J. Med. Sci.

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Section: Discussionmentioning

confidence: 99%

Machine Learning-based Correlation Study between Perioperative Immunonutritional Index and Postoperative Anastomotic Leakage in Patients with Gastric Cancer

Liu¹,

Su²,

Qi³

et al. 2022

Int. J. Med. Sci.

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“…Moreover, it can exert a positive influence on survival rates and recurrence, thereby contributing to improved patient outcomes [23]. A plethora of biomarkers have been extensively investigated to prognosticate the incidence of AL subsequent to esophagectomy [24][25][26][27][28][29][30], including C-reactive protein (CRP) or procalcitonin (PCT) [31][32][33][34][35]. Plasma cytokine levels have shown promise as potential predictors of AL [36][37][38][39] and reportedly have greater diagnostic abilities for AL, compared with CRP or PCT [37].…”

Section: Introductionmentioning

confidence: 99%

A real-world study was conducted to develop a nomogram that predicts the occurrence of anastomotic leakage in patients with esophageal cancer following esophagectomy

Li,

Song,

Zhang

et al. 2024

Aging

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Background: The incidence of anastomotic leakage (AL) following esophagectomy is regarded as a noteworthy complication. There is a need for biomarkers to facilitate early diagnosis of AL in high-risk esophageal cancer (EC) patients, thereby minimizing its morbidity and mortality. We assessed the predictive abilities of inflammatory biomarkers for AL in patients after esophagectomy. Methods: In order to ascertain the predictive efficacy of biomarkers for AL, Receiver Operating Characteristic (ROC) curves were generated. Furthermore, univariate, LASSO, and multivariate logistic regression analyses were conducted to discern the risk factors associated with AL. Based on these identified risk factors, a diagnostic nomogram model was formulated and subsequently assessed for its predictive performance. Results: Among the 438 patients diagnosed with EC, a total of 25 patients encountered AL. Notably, elevated levels of interleukin-6 (IL-6), IL-10, C-reactive protein (CRP), and procalcitonin (PCT) were observed in the AL group as compared to the non-AL group, demonstrating statistical significance. Particularly, IL-6 exhibited the highest predictive capacity for early postoperative AL, exhibiting a sensitivity of 92.00% and specificity of 61.02% at a cut-off value of 132.13 pg/ml. Univariate, LASSO, and multivariate logistic regression analyses revealed that fasting blood glucose ≥7.0mmol/L and heightened levels of IL-10, IL-6, CRP, and PCT were associated with an augmented risk of AL. Consequently, a nomogram model was formulated based on the results of multivariate logistic analyses. The diagnostic nomogram model displayed a robust discriminatory ability in predicting AL, as indicated by a C-Index value of 0.940. Moreover, the decision curve analysis provided further evidence supporting the clinical utility of this diagnostic nomogram model. Conclusions: This predictive instrument can serve as a valuable resource for clinicians, empowering them to make informed clinical judgments aimed at averting the onset of AL.

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“…Hoek et al [1] have adopted a novel variation on previous strategies by looking at the CRP trajectory over the first three postoperative days. Looking at CRP changes of >50 mg/L per day is an attractive option due to its ease, acceptability to patients and relatively low cost.…”

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confidence: 99%

Editor’s Choice – February 2022

Smart

2022

Colorectal Disease

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C‐reactive protein (CRP) trajectory as a predictor of anastomotic leakage after rectal cancer resection: A multicentre cohort study

Abstract: This is an open access article under the terms of the Creat ive Commo ns Attri butio n-NonCo mmerc ial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Cited by 5 publications

References 22 publications

Machine Learning-based Correlation Study between Perioperative Immunonutritional Index and Postoperative Anastomotic Leakage in Patients with Gastric Cancer

Machine Learning-based Correlation Study between Perioperative Immunonutritional Index and Postoperative Anastomotic Leakage in Patients with Gastric Cancer

A real-world study was conducted to develop a nomogram that predicts the occurrence of anastomotic leakage in patients with esophageal cancer following esophagectomy

Editor’s Choice – February 2022

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