Development of a clinical predictive score for allergic reactions during oral food challenges in pediatric patients

Manatchanok Pattarakiatjaroen; Araya Yuenyongviwat; Pasuree Sangsupawanich

doi:10.1371/journal.pone.0322152

Peer Review History

Original SubmissionApril 4, 2024
4 Apr 2024 Author Response https://doi.org/10.1371/journal.pone.0322152.r001
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Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: Yes ****** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: This interesting retrospective cohort study revealed the clinical predictive score for allergic reactions during oral food challenges in pediatric patients. This study concluded that the predictive score including female sex, anaphylaxis, positive skin prick testing, and specific IgE level > 2 kUA/l demonstrated a strong predictive ability for oral food challenge reactions in pediatric patients. For further clinical implications, here are my questions and suggestions. Introduction - Please overview the predictors for allergic reactions during oral food challenges identified in previous studies classified by food allergen and point out the knowledge gap leading to the hypothesis of this study. Methods - Please clearly describe the type of missing data leading to exclusion criteria. - Were there any patients receiving oral immunotherapy before the oral food challenge? - Did all patients perform skin prick tests, measurements of food-allergen-specific IgE and total IgE, and since when before the oral food challenge? Results - In demographics, please describe the types of food allergies and allergens to which the participants in this study were sensitized. - Please describe the protocol for the oral food challenge you used in your study. - How many patients had severe allergic reactions or food-induced anaphylaxis? - Please describe how you select the cut-off predictive score and the Youden index. - What is the AUC for the simple scoring model in comparison to the logistic regression model? Is it higher than a single predictor from positive skin prick testing or specific IgE? - Apart from the prediction of positive oral food challenge, can it predict the threshold dose or severity of symptoms? Discussion - Please discuss the difference you found from previous studies developing predictive models for each food allergen such as egg, wheat, and milk allergy in pediatric patients. - Please discuss the clinical implication of this predictive score Reviewer #2: The author developed the clinically predictive score for allergic reactions during OFCs in pediatric patients in a single sit. Model development by multivariable logistic regression model and assessment of the model's performance was performed appropriately using standard statistical procedures. This work merit publication. However, there are some points to be added and mentioned. 1. Concerning the generalizability, types of allergic diseases among participants undertaken OFCs should be presented in the inclusion criteria and also in the result part (table1). Allergic reaction by OFCs should be detailed and summarized, according to the system involved. 2. According to risk categorization into low and high risk by the score, the author should suggest the clinical implication for further investigation or management in patients with different risk group. For example, the low risk group is not necessary to do OFC due to low probability? 3. The final logistic regression model in this study included both serum specific IgE and skin prick test. Were both test data available for all participants in this study? Is there collinearity problem? The final model demonstrated that specific IgE>2 is not statistically significant. Moreover, in clinical practice, it might be impractical to do both specific IgE and skin test to calculate the risk score. The author should explain why the final predictive model included these two test results. ****** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean? ). If published, this will include your full peer review and any attached files. 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Revision 1
7 Jan 2025 Author Response Reviewer #1: This interesting retrospective cohort study revealed the clinical predictive score for allergic reactions during oral food challenges in pediatric patients. This study concluded that the predictive score including female sex, anaphylaxis, positive skin prick testing, and specific IgE level > 2 kUA/l demonstrated a strong predictive ability for oral food challenge reactions in pediatric patients. For further clinical implications, here are my questions and suggestions. Introduction Please overview the predictors for allergic reactions during oral food challenges identified in previous studies classified by food allergen and point out the knowledge gap leading to the hypothesis of this study. In the past, it was recommended to use the 95% positive predictive value (PPV) level for specific IgE (sIgE) or skin prick tests (SPT) to assess the risk of reactions during OFCs [3]. However, this cannot be applied practically due to differences in cutoff values across various studies [4,5]. Prior investigation has combined OFC-related variables to create predictive models for systemic reactions. DunnGalvin et al. developed a logistic regression model using six variables: total and sIgE levels, SPT wheal size, age, sex, and symptom severity [6]. Although the predictive model achieved good performance, it required measuring total IgE level, which is not typically assessed as part of routine clinical practice in preparing for OFCs. Therefore, we aimed to develop a predictive model that utilizes routine clinical data available in real-world practice by incorporating various clinical parameters, such as patient history, demographic information, and standard test results. (Add this information to the last paragraph of the introduction.) Methods Please clearly describe the type of missing data leading to exclusion criteria. Patient records with missing predictive data were excluded from the analysis. (Add this information in the methods) During the research period, a total of 214 patients underwent OFCs. However, 35 cases were excluded due to missing SPTs or specific IgE results, resulting in a sample of 179 patients for model development (Add this information in the results) Were there any patients receiving oral immunotherapy before the oral food challenge? None received oral immunotherapy prior to the oral food challenge. Did all patients perform skin prick tests, measurements of food-allergen-specific IgE and total IgE, and since when before the oral food challenge? All patients underwent skin prick tests (SPT) and specific IgE testing for suspected food allergens within one month before the oral food challenge. (Add this information in the methods) Results In demographics, please describe the types of food allergies and allergens to which the participants in this study were sensitized The data is presented in Supplement 1. Please describe the protocol for the oral food challenge you used in your study. The open OFCs were performed in accordance with PRACTALL guidelines. (Add this information in the methods) How many patients had severe allergic reactions or food-induced anaphylaxis? Four patients experienced severe reactions requiring treatment. (Add this information in the results) Please describe how you select the cut-off predictive score and the Youden index. The allergic reaction rate during OFCs for each score point is shown in Supplement 2. Data show similar rate for score 0/1 and score 2/3. Therefore, patients were stratified into two groups based on their assigned scores: 0/1 for the low-risk group and 2/3 for the high-risk group. (Add this information in the results) What is the AUC for the simple scoring model in comparison to the logistic regression model? Is it higher than a single predictor from positive skin prick testing or specific IgE? AUC of a single predictor • positive skin prick testing = 0.62 • specific IgE >2 kUA/l = 0.57 AUC of the final logistic regression = 0.71 AUC of the predictive score = 0.71 Apart from the prediction of positive oral food challenge, can it predict the threshold dose or severity of symptoms? We were unable to develop a prediction model for severe reactions due to the small number of patients with severe reactions (n=4). Discussion Please discuss the difference you found from previous studies developing predictive models for each food allergen such as egg, wheat, and milk allergy in pediatric patients. compare previous study DunnGalvin et al. [6] developed a logistic regression model aimed at predicting food allergy outcomes based on six key variables: total and specific IgE (sIgE) levels, skin prick test (SPT) wheal size, age, sex, and symptom severity. This model demonstrated strong predictive accuracy, achieving area under the curve (AUC) values of 0.97 for peanut, 0.95 for egg, and 0.94 for milk, underscoring its effectiveness. In comparison to our model, notable differences include the integration of total IgE as a predictive variable, along with the use of specific cutoffs for SPT and sIgE tailored to each type of allergenic food. A key challenge with employing these food-specific cutoffs, however, lies in the variability of cutoff values across different studies. This inconsistency can restrict the generalizability of the model’s application across various populations and clinical settings. (Add this information in discussion) Please discuss the clinical implication of this predictive score implication Based on the risk score, patients categorized in the low-risk group, with a reaction probability of 6.7%, may safely proceed with an OFC to obtain a definitive diagnosis, as their likelihood of experiencing a severe reaction is low. Conversely, for those in the high-risk group, with a reaction probability of 29.5%, the recommendation could be to delay the OFC or conduct it under close medical supervision, possibly requiring hospitalization to ensure immediate intervention if needed. This stratified approach not only aims to improve patient safety but also enhances the efficiency of managing suspected food allergies by tailoring the level of care to each patient’s risk level. (Add this information in discussion) Reviewer #2: The author developed the clinically predictive score for allergic reactions during OFCs in pediatric patients in a single sit. Model development by multivariable logistic regression model and assessment of the model's performance was performed appropriately using standard statistical procedures. This work merit publication. However, there are some points to be added and mentioned. 1. Concerning the generalizability, types of allergic diseases among participants undertaken OFCs should be presented in the inclusion criteria and also in the result part (table1). Allergic reaction by OFCs should be detailed and summarized, according to the system involved. suspected Food allergy ofc reaction. The types of allergic diseases and allergic reaction rates is presented in Supplement 1. 2. According to risk categorization into low and high risk by the score, the author should suggest the clinical implication for further investigation or management in patients with different risk group. For example, the low risk group is not necessary to do OFC due to low probability? low do high postpone Based on the risk score, patients categorized in the low-risk group, with a reaction probability of 6.7%, may safely proceed with an OFC to obtain a definitive diagnosis, as their likelihood of experiencing a severe reaction is low. Conversely, for those in the high-risk group, with a reaction probability of 29.5%, the recommendation could be to delay the OFC or conduct it under close medical supervision, possibly requiring hospitalization to ensure immediate intervention if needed. This stratified approach not only aims to improve patient safety but also enhances the efficiency of managing suspected food allergies by tailoring the level of care to each patient’s risk level. (Add this information in discussion) 3. The final logistic regression model in this study included both serum specific IgE and skin prick test. Were both test data available for all participants in this study? Is there collinearity problem? The final model demonstrated that specific IgE>2 is not statistically significant. Moreover, in clinical practice, it might be impractical to do both specific IgE and skin test to calculate the risk score. The author should explain why the final predictive model included these two test results. After comparing the model with and without sIgE, we observed no change in AUC. Given this lack of impact on predictive performance, we decided to exclude sIgE from the final model, and the results have been updated. Attachments Attachment Submitted filename: Responses to reviewers.pdf https://doi.org/10.1371/journal.pone.0322152.r003
18 Mar 2025 Decision Letter - Fatih Oz, Editor Development of a clinical predictive score for allergic reactions during oral food challenges in pediatric patients. PONE-D-24-10955R1 Dear Dr. Sangsupawanich, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. If you have any questions relating to publication charges, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Fatih Oz, Ph.D. Academic Editor PLOS ONE Additional Editor Comments (optional): Dear Authors, Thank you for revising your article based on the reviewers’ suggestions. I am pleased to confirm that your article has been accepted for publication in Plos One. Congratulations. Reviewers' comments: https://doi.org/10.1371/journal.pone.0322152.r004
Formally Accepted
Acceptance Letter - Fatih Oz, Editor PONE-D-24-10955R1 PLOS ONE Dear Dr. Sangsupawanich, I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team. At this stage, our production department will prepare your paper for publication. This includes ensuring the following: * All references, tables, and figures are properly cited * All relevant supporting information is included in the manuscript submission, * There are no issues that prevent the paper from being properly typeset If revisions are needed, the production department will contact you directly to resolve them. If no revisions are needed, you will receive an email when the publication date has been set. At this time, we do not offer pre-publication proofs to authors during production of the accepted work. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few weeks to review your paper and let you know the next and final steps. Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. If we can help with anything else, please email us at customercare@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Professor Fatih Oz Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0322152.r005

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