Revisiting sample size planning for receiver operating characteristic studies: A confidence interval approach with precision and assurance

Shu, Di; Zou, Guangyong

doi:10.1177/09622802231151210

Cited by 3 publications

(1 citation statement)

References 34 publications

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“…The AUC has become a popular index for quantifying the association between continuous variables and binary outcomes (Martínez‐Camblor et al, 2020). Extensive literature covers both theoretical and practical aspects of the ROC curve and related topics, including AUC comparison under various experimental designs, determination of sample sizes for effective AUC comparisons (Kim et al, 2014; Shu & Zou, 2023), and other related investigations (Tcheuko et al, 2016). In the original study that motivated this research, the AUC serves as a metric to capture the differences in brain states induced by an intervention in an animal model.…”

Section: Discussionmentioning

confidence: 99%

Comparing the effectiveness of k$$ k $$‐different treatments through the area under the ROC curve

Martínez‐Camblor,

Pérez‐Fernández,

Dwiel

et al. 2024

Stat

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The area under the receiver‐operating characteristic curve (AUC) has become a popular index not only for measuring the overall prediction capacity of a marker but also the strength of the association between continuous and binary variables. In the current considered study, the AUC was used for comparing the association size of four different interventions involving impulsive decision making, studied through an animal model, in which each animal provides several negative (pretreatment) and positive (posttreatment) measures. The problem of the full comparison of the average AUCs arises therefore in a natural way. We construct an analysis of variance (ANOVA) type test for testing the equality of the impact of these treatments measured through the respective AUCs and considering the random‐effect represented by the animal. The use (and development) of a post hoc Tukey's HSD‐type test is also considered. We explore the finite‐sample behaviour of our proposal via Monte Carlo simulations, and analyse the data generated from the original problem. An R package implementing the procedures is provided in the supporting information.

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Section: Discussionmentioning

confidence: 99%

Comparing the effectiveness of k$$ k $$‐different treatments through the area under the ROC curve

Martínez‐Camblor,

Pérez‐Fernández,

Dwiel

et al. 2024

Stat

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Extending the DeLong algorithm for comparing areas under correlated receiver operating characteristic curves with missing data

Zou,

Choi,

Guizzetti

et al. 2024

Statistics in Medicine

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A nonparametric method proposed by DeLong et al in 1988 for comparing areas under correlated receiver operating characteristic curves is used widely in practice. However, the DeLong method as implemented in popular software quietly deletes individuals with any missing values, yielding potentially invalid and/or inefficient results. We simplify the DeLong algorithm using ranks and extend it to accommodate missing data by using a mixed model approach for multivariate data. Simulation results demonstrate the validity and efficiency of our procedure for data missing at random. We illustrate our proposed procedure in SAS, Stata, and R using the original DeLong data.

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Pneumonitis in older lung cancer patients after radiotherapy (POLCAR): A prospective study to develop a scoring instrument that helps identify radiation pneumonitis in elderly patients with lung cancer

Rades,

Zwaan,

Ohlen

et al. 2024

Preprint

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Background: Pneumonitis caused by radiotherapy for lung cancer may be missed, since it often occurs only several months later. In a previous trial including patients of any age, a symptom-based scoring system was tested to facilitate the correct diagnosis of radiation pneumonitis. Since elderly lung cancer patients have a greater risk of developing this complication, a separate scoring system particularly for this age group appears reasonable. This trial investigates such a specific tool for elderly patients irradiated for lung cancer. Methods: Patients with lung cancer patients aged ≥65 years will be included in this prospective multi-center trial and complete paper-based questionnaires (symptom-based scoring system). Patients indicate and rate symptoms potentially caused by pneumonitis, namely cough, dyspnea, and fever, once a week during and up to 24 weeks following their radiotherapy course. If symptomatic (grade ≥2) pneumonitis is confirmed by corresponding diagnostic procedures, patients receive prednisolone whenever possible. The total score of the symptom-based scoring system, which ranges between 0 and 9 points, is correlated to pneumonitis (yes or no). The discriminative power of the scoring system is evaluated by calculating the area under the receiver operating characteristic curve (AUC). Optimality is defined as a cut-off score with sensitivity ≥90% and specificity ≥80%. In addition, the Youden index (sensitivity + specificity – 1) will be applied. Fifty-nine patients (18 with and 41 without pneumonitis) are required in the full analysis set. Assuming that 5% of the patients will not qualify for this set, 62 patients should be enrolled. In addition, patient satisfaction with the scoring system is evaluated. If the dissatisfaction rate is >20%, the score needs modifications; if the dissatisfaction rate is >40%, the scoring system is considered not useful. Discussion: If the optimal cut-off score facilitates the diagnosis of radiation pneumonitis and its discrimination from other lung diseases in elderly patients with lung cancer, it will contribute to the development of a mobile application for identification of radiation pneumonitis, which can be used by the patients at home. Trial registration: clinicaltrials.gov (NCT06480734; URL: https://clinicaltrials.gov/show/NCT06480734); protocol version 1.2, registered on 27th of June, 2024.

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Revisiting sample size planning for receiver operating characteristic studies: A confidence interval approach with precision and assurance

Cited by 3 publications

References 34 publications

Comparing the effectiveness of k$$ k $$‐different treatments through the area under the ROC curve

Comparing the effectiveness of k$$ k $$‐different treatments through the area under the ROC curve

Extending the DeLong algorithm for comparing areas under correlated receiver operating characteristic curves with missing data

Pneumonitis in older lung cancer patients after radiotherapy (POLCAR): A prospective study to develop a scoring instrument that helps identify radiation pneumonitis in elderly patients with lung cancer

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