-->PONE-D-26-05935-->-->Joint modelling of PSA dynamics and prostate cancer risks: A population-based study-->-->PLOS One

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Reviewers' comments:

Reviewer's Responses to Questions

-->Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. -->

Reviewer #1: Yes

Reviewer #2: Partly

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-->2. Has the statistical analysis been performed appropriately and rigorously? -->

Reviewer #1: Yes

Reviewer #2: Yes

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-->3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.-->

Reviewer #1: Yes

Reviewer #2: No

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-->4. Is the manuscript presented in an intelligible fashion and written in standard English?

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Reviewer #1: Yes

Reviewer #2: Yes

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-->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: The authors have analyzed PSA testing dynamics by applying a joint model of PSA values and testing patterns and risk of prostate cancer to observational data. The model identified stronger associations between PSA increase and prostate cancer diagnosis and retesting. They concluded that the joint approach is more appropriate compared to separate models and that PSA dynamics may be clinically informative.

The manuscript is well written and brings an important contribution to the field of modelling of PSA dynamics and screening. I have some (mainly minor) comments that may improve the manuscript.

Title

I suggest that you add the target population to the title – for example:

“Joint modelling of PSA dynamics and prostate cancer risks: A population-based study of men without prior prostate cancer diagnosis”

Abstract

Without having read the rest of the manuscript, it is not entirely clear how the conclusions are supported by the results presented in the abstract alone. How does the joint model correct for bias, and in what sense is it more accurate? Could this be demonstrated with results, for example by explicitly comparing it with the separate models?

Minor: I do not agree that the following is a limitation “the model does not explicitly account for PSA trajectory changes after cancer onset” considering that you aimed to model PSA dynamics in men without prior prostate cancer diagnosis. It could perhaps be mentioned as a delimitation in the discussion.

Introduction

Minor: The last paragraph – I suggest that you add the target population to the aim, for example something like this:

“In this study, we aimed to develop a detailed population-based PSA model for men without a prior prostate cancer diagnosis.”

Materials and methods

The authors state that a PSA is followed by an MRI and then possibly by a biopsy. At the same time data on men that underwent PSA testing was collected between 2003-2020. MRI was only introduced into the diagnostic pathway during the latter part of the study window. I suggest that the authors clarify how the guidelines have changed over the study period and provide details on when MRI was introduced.

Minor: Also, not all men should undergo an MRI before biopsy, so I suggest that you say that the contemporary typical diagnostic pathway is PSA – MRI – biopsy.

Minor: I would say that the paragraphs between lines 97 and 113 are results and should be moved to the results section.

Minor: what was the lower detection limit for PSA from the laboratories and did this vary over calendar time? Was there an upper reported limit for PSA? How did you handle this in the modelling?

Given the emphasis on the novelty of the modelling approach, I would have appreciated a bit more detail about the model in the main text under “Statistical methods”. For instance, how were the spline knots chosen, and how was the log transformed PSA trajectory explicitly incorporated into the subsequent Cox models?

Minor: It would also have been good with a sentence or two about how the model was fitted, and a short description of how you plan to illustrate or present the fitted model(s). This would be valuable especially to those unfamiliar with the joint/latent modelling approach.

Why did the separate models not include splines, or did they? It is not clear based on reading lines 135-139. I would have expected the separate models to be as similar as possible to the joint model in terms of how the covariates were represented.

Minor: what was the covariance matrix for the random effects in the longitudinal submodel?

Minor: supplement – I think there should be an explicit reference to the arXiv article that describes the method with the relevant identifier.

Results

The results are clearly presented. However, I believe it would be valuable to include an explicit comparison between the joint model and the separate models in the manuscript, especially since this is a key finding highlighted in both the abstract and the discussion’s summary of results. Perhaps Figures 1 and 3–4 could be combined to make space for additional details on all the models currently found in the supplement.

Minor: how come there is such a wide interval for PSA for younger ages in Figure 1? Is it for the same reason as for the later figures, or is there a larger heterogeneity in younger men?

Minor: did model performance somehow deteriorate or improve over calendar time, considering the changing diagnostic landscape and in particular the introduction of MRI?

Discussion/conclusions

Minor: consider to give an example of how the model can be used in a personalized decision-making context?

I would have appreciated a more in‑depth discussion of the modelling choices and the plausibility of the underlying assumptions. For example, the authors conclude the discussion by stating that they plan to model cancer onset and integrate it into the joint model. It would be helpful for readers to understand why this addition would be valuable—for example, in what ways might it improve model performance? Could the authors illustrate how the current model may underperform, perhaps by showing that it does not fully capture the heterogeneity and dynamics in the data over time, and how the proposed extension might address this limitation?

Reviewer #2: The endeavour to jointly model longitudinal PSA patterns based on age and retesting is of interest. The data used is appropriate and the methodology applied is overall relevant. The manuscript is well written. I have some comments and questions that may help the authors to improve the manuscript:

1. There is a substantial amount of descriptive data regarding PSA values in the methods section. This is more appropriate to present in the results section.

2. How can calendar time effects during the 17 years study period influence the results? Was calendar time handled in the modelling? If not, why not?

3. Can differences in clinical practice within the source population create correlations between different hospitals/clinics/healthcare providers?

4. How was the situation handled when the interval between the available PSA-values from an individual is very short (weeks). This could likely introduce unstable PSA trajectories.

5. What is the rationale for including the entire age range in the study population? What are the consequences of including the apparently unstable data form the extremes of the age distribution (<40 and >90) in the modelling exercises?

6. The finding that PSA doubling time is associated with an increased likelihood for a new test is not unexpected.

7. The expression in the results section that “uncertainty in the earlier parts of each trajectory (before the first measurement) is informed by future observations, providing a retrospective estimate of the patient’s past” is a bit difficult to understand the relevance of. The authors should justify the relevance of predicting a single individual’s observations, when this individual has been part of the observations used to develop the prediction model. It would likely be more relevant to display the prediction against variability of observations, and/or attempt a validation against data not used in model development, to avoid overly enthusiastic assessments of model performance.

8. The figures 3 and 4 display multiple PSA values at specific ages for single individuals, and for the man diagnosed with prostate cancer, the specific age at diagnosis. This appears as information that risk being able to identify specific individuals. Please verify that such presentation of data is compatible with the ethical approval and protection of personal integrity.

9. The results presentation regarding validation of the model predictions appears limited and not in line with guidelines for reporting of prediction models. Please review relevant guidelines and preferably improve adherence to these.

10. In the discussion it is stated that “The mean age at diagnosis was 70.8 years, which explains the higher PSA densities observed among men aged 60 and older, likely reflecting cancers that had already developed by that age”. There is, however, no mentioning of data on PSA density in the methods and results sections. Please clarify.

11. An important concern with the current manuscript is that the results presentation and discussion allude to use of the models for individual level predictions. The validation of the models does not substantiate such claims. If the models are intended for use on the individual level a much more elaborate validation is expected, with robust support for external validity. An important restriction is how to describe and communicate the uncertainty of model predictions on the individual level. As currently presented, claims for individual level predictions have not been justified, and either the analyses should be substantially expanded or these claims be removed. The statement that “This approach scaled well to a moderately large dataset and supported personalised predictions, including measures of uncertainty” is not agreed.

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Reviewer #1: No

Reviewer #2: No

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Joint modelling of PSA dynamics and prostate cancer risks: A population-based study in men without prior prostate cancer

PONE-D-26-05935R1

Dear Dr. B. Akynkozhayev

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.

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Kind regards,

Stanisław Jacek Wroński, M.D., Ph.D, FEBU

Academic Editor

PLOS One

Reviewers' comments:

Reviewer's Responses to Questions

-->Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.-->

Reviewer #2: All comments have been addressed

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-->2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. -->

Reviewer #2: (No Response)

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-->3. Has the statistical analysis been performed appropriately and rigorously? -->

Reviewer #2: (No Response)

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-->4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.-->

Reviewer #2: (No Response)

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-->5. 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 #2: (No Response)

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-->6. 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 #2: (No Response)

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Reviewer #2: Yes: Rolf Gedeborg

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