Powering Research through Innovative Methods for Mixtures in Epidemiology (PRIME) Program: Novel and Expanded Statistical Methods

Round 1

Reviewer 1 Report

The submitted manuscript summarizes 36 new statistical methods recently developed in several research projects under the scope of Powering Research through Innovative Methods for mixtures in Epidemiology (PRIME) Program funded by the National Institute of Environmental Health Sciences (NIEHS). The exposition of humans to different kinds of pollution mixtures is having an impact on public health. However, there is a lack of statistical tools for their application in common epidemiological scenarios, which allow substantiating relationships with available information. NIEHS PRIME Program methods have been developed to address challenges related to data analysis in environmental mixtures research as overall effect estimation, toxic agent identification, pattern identification, a priori defined groups, and interactions and non-linearities. In addition, the authors take into account other aspects related to datasets, method performance, exposure-response estimation, and risk assessment and regulatory relevance. Finally, all methods are on open source platforms, and both packages and functions are available to the scientific community.

The topic of this manuscript is of interest, mixtures represent the most common form of contamination, and the availability of statistical methods that can accurately manage datasets is an essential part of epidemiology and public health. Although the presented methods are already published, this review is the first to introduce and summarize them together, allowing for a global vision of the latest advances in this field. The information is clear and concise, and it is also well organized. Therefore, after reviewing the manuscript, I recommend the Editor´s acceptance for publication in present form.

Author Response

We thank the reviewer for these positive comments and time reviewing the paper. Regarding the note on English language revisions, we have carefully reviewed the text with regards to grammar and made corrections and improvements in the revision. 

Reviewer 2 Report

 General comments:

The review manuscript entitled “Powering Research through Innovative Methods for mixtures in Epidemiology (PRIME) Program: Novel and expanded statistical methods” was reviewed. The work carried out in the manuscript is interesting and informative for readers and related researchers.  However, the authors are suggested to undergo some corrections before possible publication.

Detailed comments:

Title: Ok.

Abstract:

The abstract does not work well. It narrates activities. A good abstract should address these issues: what are you trying to do, why, what you found and what is the significance of your findings. Should be more outcome-oriented.

Introduction:

The review of literature is very well written.

Discussion:

All the findings of the current work need to be compared and discussed with the results of other researchers' findings instead of having a general comparison with other researchers' works. The authors should perform a comparison between the forecasting results.

Conclusions:

The conclusion section appears to be just a detailed summary of results/observations and must go deeper (this should not be another Abstract).

References:

Fair enough.

Comments for author File: Comments.pdf

Author Response

We thank the reviewer for their valuable comments and time reviewing the paper. Please see responses in the attached document. 

Author Response File: Author Response.docx