Development and Validation of a Nomogram Predicting the Probability of in Hirschsprung Children Following Surgery

NCT06025188 | Completed

• 1 other identifier: TJH-DVNPPH
• Study Type: observational
• Target: 600
• Locations: 1 country
• Sites: 1

Brief Summary

Postoperative soiling is a common complication following Hirschsprung disease \[HSCR\] surgery. The aim of this study was to develop a nomogram for predicting the probability of postoperative soiling in patients aged \>1 year operated for HSCR. The investigators retrospectively analyzed HSCR patients with surgical therapy over one year of age from January 2000 and December 2019 at our department. Eligible patients were randomly categorized into the training and validation set at a ratio of 7:3. By integrating the least absolute shrinkage and selection operator \[LASSO\] and multivariable logistic regression analysis, crucial variables were determined for establishment of nomogram. And, the performance of nomogram was evaluated by C-index，area under the receiver operating characteristic curve \[ROC\], calibration curves, and decision curve analysis \[DCA\]. Meanwhile, a validation set was used to further assess the model.

Conditions

Develop a Nomogram

Outcome Measures

Primary Outcomes (1)

• Harrell's concordance index (C-index)

  Harrell's concordance index \[C-index\] was generated to estimate the discrimination of the nomogram A C-index close to 1 indicates a high level of predictive ability of the model.

  1 month

Study Arms (2)

training set

To determine potential predictive factors, the training set was subjected to LASSO regression analysis, which effectively eliminated several irrelevant or multicollinearity independent variables to reduce high-dimensional data

Other: training set

validation set

The multivariable logistic regression analysis was applied to determine the variables of soiling in patients with HSCR following surgery over one year of age. Finally, a nomogram was created based on the training set and validated in the validation set.

Other: training set

Interventions

training set OTHER

LASSO regression analysis, Logistic regression analysis, Nomogram

training set; validation set

Eligibility Criteria

• Age: 1 Year+
• Gender Eligibility Details: patients aged \>1 year operated for HSCR.
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

This retrospective study was conducted on patients diagnosed with HSCR who underwent surgical treatment at our hospital department from January 2000 to December 2019.

You may qualify if:

• Patients were experienced soiling persisting for more than 6 months following surgery.
• Patients aged \>1 year, gender is not limited. The patient must sign an informed consent form and can actively cooperate with the treatment and follow-up.

You may not qualify if:

• Patients with other severe deformity. Patients with mental symptoms or other disease. patients who had their initial surgery at another institution.

Sponsors & Collaborators

• Tongji Hospital: lead

Study Sites (1)

Tongji hospital affiliated to tongji medical college of huazhong university of science and technology

Wuhan, Hubei, 430030, China

Location

Related Publications (1)

• Wang P, Fang E, Zhao X, Feng J. Nomogram for soiling prediction in postsurgery hirschsprung children: a retrospective study. Int J Surg. 2024 Mar 1;110(3):1627-1636. doi: 10.1097/JS9.0000000000000993.

  PMID: 38116670 DERIVED

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Chief in Department

Study Record Dates

• First Submitted: August 25, 2023
• First Posted: September 6, 2023
• Study Start: July 1, 2021
• Primary Completion: August 1, 2021
• Study Completion: August 1, 2022
• Last Updated: September 6, 2023

Record last verified: 2023-09

Locations

CN (1)