The DGAV risk calculator: development and validation of statistical models for a web-based instrument predicting complications of colorectal cancer surgery

Crispin, Alexander; Klinger, Carsten; Rieger, Anna; Strahwald, Brigitte; Lehmann, Kai S.; Buhr, H. J.; Mansmann, Ulrich

doi:10.1007/s00384-017-2869-6

Cited by 11 publications

(18 citation statements)

References 14 publications

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“…Future studies should develop a user-friendly tool for risk score calculations and evaluate prospectively whether the proposed prediction strategy is effective in guiding favorable BMI growth in early childhood. Such a tool should be easy-to-use in clinical practice, and results should be communicated in an informative manner [ 100 , 101 ], e.g., a web-based Shiny application developed using the Shiny R package for building easy and interactive web apps in R [ 102 ]. Implementing such an instrument and designing a prospective validation study are plans for our future research.…”

Section: Discussionmentioning

confidence: 99%

Predicting the earliest deviation in weight gain in the course towards manifest overweight in offspring exposed to obesity in pregnancy: a longitudinal cohort study

Gomes

Perschbacher

et al. 2022

BMC Med

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Background Obesity in pregnancy and related early-life factors place the offspring at the highest risk of being overweight. Despite convincing evidence on these associations, there is an unmet public health need to identify “high-risk” offspring by predicting very early deviations in weight gain patterns as a subclinical stage towards overweight. However, data and methods for individual risk prediction are lacking. We aimed to identify those infants exposed to obesity in pregnancy at ages 3 months, 1 year, and 2 years who likely will follow a higher-than-normal body mass index (BMI) growth trajectory towards manifest overweight by developing an early-risk quantification system. Methods This study uses data from the prospective mother-child cohort study Programming of Enhanced Adiposity Risk in CHildhood–Early Screening (PEACHES) comprising 1671 mothers with pre-conception obesity and without (controls) and their offspring. Exposures were pre- and postnatal risks documented in patient-held maternal and child health records. The main outcome was a “higher-than-normal BMI growth pattern” preceding overweight, defined as BMI z-score >1 SD (i.e., World Health Organization [WHO] cut-off “at risk of overweight”) at least twice during consecutive offspring growth periods between age 6 months and 5 years. The independent cohort PErinatal Prevention of Obesity (PEPO) comprising 11,730 mother-child pairs recruited close to school entry (around age 6 years) was available for data validation. Cluster analysis and sequential prediction modelling were performed. Results Data of 1557 PEACHES mother-child pairs and the validation cohort were analyzed comprising more than 50,000 offspring BMI measurements. More than 1-in-5 offspring exposed to obesity in pregnancy belonged to an upper BMI z-score cluster as a distinct pattern of BMI development (above the cut-off of 1 SD) from the first months of life onwards resulting in preschool overweight/obesity (age 5 years: odds ratio [OR] 16.13; 95% confidence interval [CI] 9.98–26.05). Contributing early-life factors including excessive weight gain (OR 2.08; 95% CI 1.25–3.45) and smoking (OR 1.94; 95% CI 1.27–2.95) in pregnancy were instrumental in predicting a “higher-than-normal BMI growth pattern” at age 3 months and re-evaluating the risk at ages 1 year and 2 years (area under the receiver operating characteristic [AUROC] 0.69–0.79, sensitivity 70.7–76.0%, specificity 64.7–78.1%). External validation of prediction models demonstrated adequate predictive performances. Conclusions We devised a novel sequential strategy of individual prediction and re-evaluation of a higher-than-normal weight gain in “high-risk” infants well before developing overweight to guide decision-making. The strategy holds promise to elaborate interventions in an early preventive manner for integration in systems of well-child care.

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Section: Discussionmentioning

confidence: 99%

Predicting the earliest deviation in weight gain in the course towards manifest overweight in offspring exposed to obesity in pregnancy: a longitudinal cohort study

Gomes

Perschbacher

et al. 2022

BMC Med

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“…Methods for model development were heterogeneous with multivariable logistic regression (MVLR) featuring most frequently (8/12 colonic/colorectal ALPS and 18/19 rectal ALPS) with or without methods to enhance calibration such as ridge regression or LASSO (least absolute shrinkage and selection operator) (4/31 ALPS)19–21; these methods are employed to reduce model overfit 22 23. Other authors employed: systematic review methodology with meta-analysis of risk factors (using individual patient data24 or pooling ORs from individual studies25); systematic review with Delphi consensus for factor value (1/31)26; or machine learning (2/31) 27 28.…”

Section: Resultsmentioning

confidence: 99%

Systematic review of preoperative and intraoperative colorectal Anastomotic Leak Prediction Scores (ALPS)

et al. 2023

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ObjectiveTo systematically review preoperative and intraoperative Anastomotic Leak Prediction Scores (ALPS) and validation studies to evaluate performance and utility in surgical decision-making. Anastomotic leak (AL) is the most feared complication of colorectal surgery. Individualised leak risk could guide anastomosis and/or diverting stoma.MethodsSystematic search of Ovid MEDLINE and Embase databases, 30 October 2020, identified existing ALPS and validation studies. All records including >1 risk factor, used to develop new, or to validate existing models for preoperative or intraoperative use to predict colorectal AL, were selected. Data extraction followed CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies guidelines. Models were assessed for applicability for surgical decision-making and risk of bias using Prediction model Risk Of Bias ASsessment Tool.Results34 studies were identified containing 31 individual ALPS (12 colonic/colorectal, 19 rectal) and 6 papers with validation studies only. Development dataset patient populations were heterogeneous in terms of numbers, indication for surgery, urgency and stoma inclusion. Heterogeneity precluded meta-analysis. Definitions and timeframe for AL were available in only 22 and 11 ALPS, respectively. 26/31 studies used some form of multivariable logistic regression in their modelling. Models included 3–33 individual predictors. 27/31 studies reported model discrimination performance but just 18/31 reported calibration. 15/31 ALPS were reported with external validation, 9/31 with internal validation alone and 4 published without any validation. 27/31 ALPS and every validation study were scored high risk of bias in model analysis.ConclusionsPoor reporting practices and methodological shortcomings limit wider adoption of published ALPS. Several models appear to perform well in discriminating patients at highest AL risk but all raise concerns over risk of bias, and nearly all over wider applicability. Large-scale, precisely reported external validation studies are required.PROSPERO registration numberCRD42020164804.

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“…Colorectal cancer is a serious threat to public health, and surgical treatment has become the first option [ 17 ]. Laparoscopic radical resection for rectal cancer has been widely used, but the assisted incision in the abdominal wall could induce great trauma to the patients, which was not conducive to the postoperative recovery of the patient [ 18 , 19 ]. In recent years, with the development of minimally invasive technique, NOSES has become one of the most popular producers, which has the advantages of less trauma, shorter scar, shorter healing time, and fewer complications [ 20 , 21 ].…”

Section: Discussionmentioning

confidence: 99%

Long-term oncologic outcomes of natural orifice specimen extraction surgery versus conventional laparoscopic-assisted resection in the treatment of rectal cancer: a propensity-score matching study

Xiong

Qiao

et al. 2022

BMC Surg

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Background Natural orifice specimen extraction surgery (NOSES) has been increasingly applied in radical surgery of abdominal and pelvic organs, but it is still in the exploratory stage. There is insufficient evidence to prove its efficacy. Methods From January 2013 to June 2017, a total of 351 patients diagnosed with rectal cancer were eventually included in this study. Patients who underwent NOSES were assigned to the NOSES group, while patients undergoing conventional laparoscopic assisted resection were assigned as to the LAP group. Propensity score matching was used to align clinicopathological features between the two groups. Results From the perioperative data and postoperative follow-up results of both groups, patients in the NOSES group had less intraoperative bleeding (47.0 ± 60.4 ml vs 87.1 ± 101.2 ml, P = 0.011), shorter postoperative gastrointestinal recovery (50.7 ± 27.3 h vs 58.6 ± 28.5 h, P = 0.040), less postoperative analgesic use (36.8% vs 52.8%, P = 0.019), lower postoperative pain scores (P < 0.001), lower rate of postoperative complications (5.7% vs 15.5%, P = 0.020), more satisfaction with body image (P = 0.001) and cosmesis (P < 0.001) postoperatively. The NOSES group had a higher quality of life. Moreover, there was no significant difference in overall survival (OS) and disease-free survival (DFS) between the two groups. Conclusion NOSES could be a safe and reliable technique for radical resection of rectal cancer, with better short-term outcomes than conventional laparoscopy, while long-term survival is not significantly different from that of conventional laparoscopic surgery.

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The DGAV risk calculator: development and validation of statistical models for a web-based instrument predicting complications of colorectal cancer surgery

Cited by 11 publications

References 14 publications

Predicting the earliest deviation in weight gain in the course towards manifest overweight in offspring exposed to obesity in pregnancy: a longitudinal cohort study

Predicting the earliest deviation in weight gain in the course towards manifest overweight in offspring exposed to obesity in pregnancy: a longitudinal cohort study

Systematic review of preoperative and intraoperative colorectal Anastomotic Leak Prediction Scores (ALPS)

Long-term oncologic outcomes of natural orifice specimen extraction surgery versus conventional laparoscopic-assisted resection in the treatment of rectal cancer: a propensity-score matching study

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