The use of rigorous methods was strongly warranted among prognostic prediction models for obstetric care

Tan, Jing; Qi, Yana; Liu, Chunrong; Xiong, Yiquan; He, Qiao; Zhang, Guiting; Chen, Meng; He, Guolin; Wang, Wen; Liu, Xinghui; Sun, Xin

doi:10.1016/j.jclinepi.2019.07.009

Cited by 4 publications

(9 citation statements)

References 49 publications

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“…The PubMed database was searched to identify eligible literature published in selected journals from January 1, 2011, to December 31, 2020, given that few prediction models were published before 2011. A consistent search period was conducted with our series of studies [ 28 ]. The selected journals included six general medicine journals ( NEJM, Lancet, JAMA, BMJ, Ann of Intern Med, and PLoS Med ) as a sample of leading general medicine journals and the top 15% of journals according to the impact factor of the Science Citation Index for Obstetrics and Gynecology in 2016, which was also consistent with our previous study [ 28 ].…”

Section: Methodsmentioning

confidence: 99%

“…A consistent search period was conducted with our series of studies [ 28 ]. The selected journals included six general medicine journals ( NEJM, Lancet, JAMA, BMJ, Ann of Intern Med, and PLoS Med ) as a sample of leading general medicine journals and the top 15% of journals according to the impact factor of the Science Citation Index for Obstetrics and Gynecology in 2016, which was also consistent with our previous study [ 28 ]. MeSH terms and free-text keywords were used for literature searching, and the search language was limited to English (Additional file 1 ).…”

Section: Methodsmentioning

confidence: 99%

“…Following our previous study [ 28 ], if more than one prediction model was reported in a study, we chose the primary model claimed by the authors; otherwise, the first reported model was included. Details on a number of general characteristics were extracted, including (1) first author, (2) country of first author, (3) publication year, (4) publication journal, (5) predicted outcome, (6) involvement of any epidemiologist or statistician, (7) number of study sites, (8) study design, and (9) data source.…”

Section: Methodsmentioning

confidence: 99%

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The reporting of prognostic prediction models for obstetric care was poor: a cross-sectional survey of 10-year publications

Liu

et al. 2023

BMC Med Res Methodol

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Background To investigate the reporting of prognostic prediction model studies in obstetric care through a cross-sectional survey design. Methods PubMed was searched to identify prognostic prediction model studies in obstetric care published from January 2011 to December 2020. The quality of reporting was assessed by the TRIPOD checklist. The overall adherence by study and the adherence by item were calculated separately, and linear regression analysis was conducted to explore the association between overall adherence and prespecified study characteristics. Results A total of 121 studies were included, while no study completely adhered to the TRIPOD. The results showed that the overall adherence was poor (median 46.4%), and no significant improvement was observed after the release of the TRIPOD (43.9 to 46.7%). Studies including both model development and external validation had higher reporting quality versus those including model development only (68.1% vs. 44.8%). Among the 37 items required by the TRIPOD, 10 items were reported adequately with an adherence rate over of 80%, and the remaining 27 items had an adherence rate ranging from 2.5 to 79.3%. In addition, 11 items had a report rate lower than 25.0% and even covered key methodological aspects, including blinding assessment of predictors (2.5%), methods for model-building procedures (4.5%) and predictor handling (13.5%), how to use the model (13.5%), and presentation of model performance (14.4%). Conclusions In a 10-year span, prognostic prediction studies in obstetric care continued to be poorly reported and did not improve even after the release of the TRIPOD checklist. Substantial efforts are warranted to improve the reporting of obstetric prognostic prediction models, particularly those that adhere to the TRIPOD checklist are highly desirable.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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The reporting of prognostic prediction models for obstetric care was poor: a cross-sectional survey of 10-year publications

Liu

et al. 2023

BMC Med Res Methodol

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“…For instance, more than 50% of the models were developed without any validation, 22% did not specify the intended timing of use, and 12% had a small sample size (less than 200). 11 Failure to meet methodological standards can significantly compromise the credibility of resulting models. 12,13 Meanwhile, development and validation of a credible prognostic prediction model usually involve the use of sophisticated statistical methods.…”

Section: Introductionmentioning

confidence: 99%

“…In a previous study, we revealed several important methodological limitations in the study design and data collection about these models. For instance, more than 50% of the models were developed without any validation, 22% did not specify the intended timing of use, and 12% had a small sample size (less than 200) 11 . Failure to meet methodological standards can significantly compromise the credibility of resulting models 12,13 …”

Section: Introductionmentioning

confidence: 99%

Investigation of statistical methods used in prognostic prediction models for obstetric care: A 10 year‐span cross‐sectional study

Tan,

Liu,

Yang

et al. 2023

Acta Obstet Gynecol Scand

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IntroductionObstetric care is a highly active area in the development and application of prognostic prediction models. The development and validation of these models often require the utilization of advanced statistical techniques. However, failure to adhere to rigorous methodological standards could greatly undermine the reliability and trustworthiness of the resultant models. Consequently, the aim of our study was to examine the current statistical practices employed in obstetric care and offer recommendations to enhance the utilization of statistical methods in the development of prognostic prediction models.Material and methodsWe conducted a cross‐sectional survey using a sample of studies developing or validating prognostic prediction models for obstetric care published in a 10‐year span (2011–2020). A structured questionnaire was developed to investigate the statistical issues in five domains, including model derivation (predictor selection and algorithm development), model validation (internal and external), model performance, model presentation, and risk threshold setting. On the ground of survey results and existing guidelines, a list of recommendations for statistical methods in prognostic models was developed.ResultsA total of 112 eligible studies were included, with 107 reporting model development and five exclusively reporting external validation. During model development, 58.9% of the studies did not include any form of validation. Of these, 46.4% used stepwise regression in a crude manner for predictor selection, while two‐thirds made decisions on retaining or dropping candidate predictors solely based on p‐values. Additionally, 26.2% transformed continuous predictors into categorical variables, and 80.4% did not consider nonlinear relationships between predictors and outcomes. Surprisingly, 94.4% of the studies did not examine the correlation between predictors. Moreover, 47.1% of the studies did not compare population characteristics between the development and external validation datasets, and only one‐fifth evaluated both discrimination and calibration. Furthermore, 53.6% of the studies did not clearly present the model, and less than half established a risk threshold to define risk categories. In light of these findings, 10 recommendations were formulated to promote the appropriate use of statistical methods.ConclusionsThe use of statistical methods is not yet optimal. Ten recommendations were offered to assist the statistical methods of prognostic prediction models in obstetric care.

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Should we use composite outcomes in obstetric clinical prediction models?

Giles-Clark

Skinner

Rolnik

et al. 2023

European Journal of Obstetrics & Gynecology and Reproductiv

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The use of rigorous methods was strongly warranted among prognostic prediction models for obstetric care

Cited by 4 publications

References 49 publications

The reporting of prognostic prediction models for obstetric care was poor: a cross-sectional survey of 10-year publications

The reporting of prognostic prediction models for obstetric care was poor: a cross-sectional survey of 10-year publications

Investigation of statistical methods used in prognostic prediction models for obstetric care: A 10 year‐span cross‐sectional study

Should we use composite outcomes in obstetric clinical prediction models?

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