PONE-D-20-34900

Mapping Expanded Prostate Cancer Index Composite to EQ5D Utilities to Inform Economic Evaluations in Prostate Cancer: Secondary Analysis of NRG/RTOG 0415

PLOS ONE

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"Drs. Khairnar, Albert, Bentzen, Bruner, Chen, Currey, Dayes, DeNittis, Horwitz, Lee, Michalski, Mullins, Palumbo, Pisansky, Seaward, Shah, Shaya, and Villalonga have nothing to disclose. Dr. Feng reports personal fees from Janssen Oncology, Sanofi, Bayer, Celgene, and Blue Earth Diagnostics, grants from Zenith Epigenetics, and other from PFS Genomics, outside the submitted work; Dr. Malone reports personal fees from Sanofi, and honoraria from Amgen, Abbvie, Astellas, Janssen, Tersara, Astra Zeneca, Knight Therapeutics, and Bayer, outside the submitted work; Dr. Mishra reports grants from American Society of Radiation Oncology (ASTRO), during the conduct of the study and other from Varian Medical Systems, outside the submitted work; Dr. Sandler reports grants from ACR/NRG Oncology, during the conduct of the study; personal fees from Janssen, other from Radiogel, outside the submitted work; Dr. Pugh reports other from Millennium, other from Pfizer, outside the submitted work. "

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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: No

Reviewer #2: Yes

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

Reviewer #1: No

Reviewer #2: Yes

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Reviewer #1: No

Reviewer #2: No

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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: Mapping prostate cancer index

General comments:

* replace everywhere "external validation" by "test sample", this is the sample for internal validation.

Refer to the first sample as the "estimation sample", this is the equivalent to a training sample in data science also called the hold out sample

external validation implies the use of an independent external data sample which is not the case here

(see https://en.wikipedia.org/wiki/Training,_validation,_and_test_sets)

* replace everywhere in the text EQ5D by EQ-5D-3L as this is the version of the PBM questionnaire

METHODS

Sample Selection :

* Shortly describe the sample and the original data plus QoL results of the original article

* correct the naming of the samples (see above)

Outcome measures :

* specify which value set (Tariff) was used to value the EQ-5D-3L data

* I am not sure what you mean by "not part of the descriptive system"; death is anchored at zero and states worse than death can take negative values up to a lower limit , depending on the country specific Tariff used .

Model Development :

* line 160: this is wrong; OLS assumption implies that the errors (conditional on the explanatory variables) is normally distributed. This allows inference of the coefficients and tests of significance based on Normal Theory.

*Put the detailed list of the model specifications in an appendix

* line 173: higher second and third order polynomials

* which stepwise variable selection was used ? It seems it was a simple forward selection method based on the p-value. what was the criterion used to include/retain a variable ?

(see Forward selection is a type of stepwise regression which begins with an empty model and adds in variables one by one. In each forward step, you add the one variable that gives the single best improvement to your model.Sep 19, 2017

* line 166 the exact two-step method should be more detailed

was logistic regression used for the full health, what was its accuracy ?

how was the goodness of fit of the combined parts estimated utilities then further assessed ?

Were there any U values = 1 or higher resulting form the OLS regression part ? how were these dealth with ?

Forward Selection: Definition - Statistics How To

www.statisticshowto.com › forward-selection

Stepwise regression - Wikipedia "en.wikipedia.org › wiki › Stepwise_regression"

see Variable Selection www.biostat.jhsph.edu › ~iruczins › teaching

and for a discussion and limitations of the different methods

Loann. D. Desboulets , A Review on Variable Selection in Regression Analysis Econometrics, 2018

The results of the forward regresson methods should be confrmed by another selection method, especially since the n/p (observations/parameters) ratio is rather low in the regression incorporating interactions and power variables.

A LASSO type or similar method would be useful in this situation. It can be applied to the full most detailed equation including all subscales and interactions/power variables.

Assessing Model Performance :

The choice of only the RMSE as accuracy criterion (Goodness of fit) is not to be recommended , it should be complemented by other criteria as well including MAE, estimated utility values >1 and <0, etc...

I would urge the authors to also present a Bland-Altman plot of the results of their best fitting model (with 95% confidence intervals and minimally clinically important limits as well for EQ-5D utilities +- 0.08)

Also the multiple comparison problem given the hughe number of regressions performed should be discussed/adressed .

Five-fold cross-validation was used , I guess this was on the test sample ? how were the regression results then combined ? give some more details about the exact procedure followed to allow replication of your methodology by others.

RESULTS

Descriptive Statistics :

* Include the results of a statistical comparison test of the variables between the different samples in table 2 and table 3 to assess their similarity of the samples

* given the highly bimodal nature of the observed utilities non-parametric summary measures (medians, IQR, etc..) and test statistics should be preferred added to the tables

Mapping results :

* show first the tables of performance and selection of the best fitting equations

then show the detailed equation of the best fitting one(s)

A likelihood ratio test should be performed to compare the reduced equation and the full equation of the predicted 5EQ-5D as these are nested. If the H0 of equality is not rejected (in the testing sample) then the full equation can be dropped

* present the regression coefficients with their 95% CI and present aso the variance-covariance matrix of the regression parameters

DISCUSSION

line 316 which generic PBM did Bremen used ? specify

how bad was the underprediction of low observed utilities ? where was the utility threshold ?

how bad was the overprediction for observed high utilities ? where was the utility threshold ?

What was the variance of the estimates compaed to the observed variance of utilities for different values of utilities (low, average ,high, perfect health) or per quartile?

line 338: your risk of bias is linked to whether the censoring and non-response to the QoL questionnaires was truly random otherwise there is a risk of "survival or response" bias. Nothing tells you that the non responders had the same mapping coefficients as those of the completers so this could potentially alter the regression coefficients.

Reviewer #2: This paper has examined three econometric models for estimating EuroQol- 5 Dimension (EQ-5D) utility scores from the Expanded Prostate Cancer Index Composite (EPIC) to calculate quality adjusted life years for cost-utility analysis. The paper uses robust methods that should act as an aid for utility estimation within future economic evaluations of interventions using the Expanded Prostate Cancer Index Composite in Prostate Cancer. As such, it has the potential to act as a beneficial addition to the mapping literature. This article is well written, and the authors have carefully followed standard mapping methodology.

Major comments:

1. Abstract Page 3, Line 51: The authors state that the lack of health utilities associated with the different health states assessed with the EPIC are unknown, therefore limiting the ability to perform cost-effectiveness evaluations. Can the authors edit this and use cost-utility analysis (CUA) and not cost-effectiveness analysis (CEA) as the form of economic evaluation which allows for the comparison of alternative treatment options in terms of incremental costs relative to quality-adjusted life-years (QALY) gained following treatment is a cost-utility analysis.

2. Abstract Page 3, Line 52: The authors use the term "utility weights". This term is used in valuation studies when generating population preference weights or scoring algorithms and not mapping algorithms. The authors should correct this and use utility scores or utilities instead.

3. Page 6: The authors present mapping as though the reader might already know what it is. Can the authors provide a more detailed definition of what mapping is.

4. Page 8 Line 162: Several other estimators have been applied in the mapping literature, including Fractional Logistic regression (FLOGIT); Censored Least Absolute Deviations (CLAD) regression; Generalized Additive Models; and finite mixture models. There are critics of the Tobit estimators, for example, but why haven't finite mixture models been applied?

5. Details of ethics committee approvals should be provided.

6. Model selection should not be based solely upon the criteria, such as the predictive accuracy of on root mean square error (RMSE), laid out on page 12. The paper would be strengthened by a formal and staged selection process employed to choose between the models, including the BIC, AIC (for models for which the likelihood can be computed), misspecification tests, comparisons of conditional means or other similarly informative measures. These should dictate both the choice of covariates as well as the selection across different models.

7. Page 15, When assessing model performance: the errors should also be reported across subsets of the EQ5D utility score range as this is useful for indicating whether or not there is systematic bias in the predictions.

8. External validation is the preferred method for ascertaining the predictive accuracy of a mapping model. The authors of this paper use in-sample validation methods. Can the authors provide a detailed explanation of what a "five-fold cross-validation" is and how the in-sample validation datasets were generated? Secondly, how did they ensure that 'overfitting' was not an issue in the validation exercise? Thirdly, can the authors comment on how adequate five-fold cross-validation is as opposed to say ten-fold validation which has been in several mapping studies.

Minor comments:

1. Figure S1A: Please correctly label x-axis EQ5D and not EQ5D0

2. Page 8 Line 154: Please correct HRQOL to HRQoL

3. The paper does not seem to fully get across that mapping is a second-best solution and that having original data collected from relevant populations is a better solution. For the uninitiated, they may believe that EPIC data collected from patients with PC can be converted to EQ5D utilities "with a high level of accuracy". Hence, there is no need to collect original utility data.

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Reviewer #1: No

Reviewer #2: No

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Mapping Expanded Prostate Cancer Index Composite to EQ5D Utilities to Inform Economic Evaluations in Prostate Cancer: Secondary Analysis of NRG/RTOG 0415

PONE-D-20-34900R1

Dear Dr. Mishra,

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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Additional Editor Comments (optional):

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 #1: All comments have been addressed

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 #1: Yes

Reviewer #2: Yes

**********

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

Reviewer #1: Yes

Reviewer #2: Yes

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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 #1: No

Reviewer #2: No

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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 #1: Yes

Reviewer #2: Yes

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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 #1: (No Response)

Reviewer #2: The authors have addressed the points raised in my previous review, and publication of the manuscript as is recommended.

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Reviewer #1: No

Reviewer #2: No