PONE-D-20-35238

Optimal Treatment Strategies for Stage I Non-small Cell Lung Cancer in Veterans with Pulmonary and Cardiac Comorbidities

PLOS ONE

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Hyun-Sung Lee, M.D., Ph.D.

Academic Editor

PLOS ONE

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Reviewers' comments:

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Comments to the Author

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

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Reviewer #1: Partly

Reviewer #2: Yes

Reviewer #3: Yes

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

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #1: No

Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: 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: This observational study utilized national VA data to simulate differences in outcomes for Veterans treated with surgery or SBRT according to age and comorbidities. The manuscript over-interprets the findings to suggest that these data can be used to guide clinical management. Recommendations are made below to present the data in a more appropriate and scientific manner. A key data input was missing (Boyer et al JTO 2017)

Abstract background: it isn’t possible to identify the “optimal management” from an observational dataset. Please state a more appropriate objective for this study that considers the limitations and discloses that its aim is to find associations with outcomes. It’s important that this paper does not assert itself as a guide for clinical practice and to be clear that it is only hypothesis-generating.

Abstract results: please use a more scientific term instead of “the best”. Ensure it reflects the finding of an association without suggesting causality. Next, provide more specific about what outcome measure was superior.

Abstract conclusion: please change “varies” to “may vary”. Next, the last sentence is unacceptable as the findings of this simulation modeling can, at most, guide future research study design.

Line 83: to avoid suggestions of causality, please change “worse” to “lower”

Line 93: please balance this statement with at least one reference that states the opposite (e.g. Robinson et al JTO 2013) and also studies that show OS might not be different with SBRT (e.g. Shirvani et al JAMA 2014) or limited resection (numerous)

Line 96: Please clarify that clinical trials data may be relevant for some Veterans, but not for all. As written, it suggests all Veterans have serious comorbidities.

Line 104: it’s unclear what is meant by “evaluate different therapeutic options”. Is this to predict outcomes from a simulated model? Or, to use a complex model to summarize outcomes that occurred in the past? This clarification will be appreciated by readers.

Line 119: please clarify what national VA sources were identified. Be specific as there are many, each with their respective limitations that have been published on. Clarify if the model pulled data from publications (as suggested in Table 1). Please clarify what domains from the VA’s CDW were accessed. Please disclose the authorizations obtained to access these non-publicly available data.

Line 130: Boyer et al JTO 2017 is a critical input that is missing here. That study, through 2010, identified over 400 pts treated with SBRT. Please clarify the reason for this discrepancy as this report only identified 386 pts though 2015.

Line 213: the tempered and scientific summary of results in this paragraph are appropriate and can serve as a model to summarize other findings to avoid over-interpretation elsewhere in the results section and discussion

Line 258: the term “benefits” suggests causality. Please substitute.

Line 287: statements about optimal treatments cannot be made from these observational data. One can

only summarize what covariates are associated with an outcome

Line 289: the term “maximized” suggests causality. Please use terms that clarify the discovery of associations.

Line 290: please substitute a more appropriate term for “benefited”

Line 295: the term “best” isn’t qualified. Please change or remove

Line 300: please acknowledge the value of the STS prospective database

Line 306: “led to maximal” suggests causality. Please change.

Line 320: please find a more suitable term than “benefited” to avoid suggestion of causality

Line 321: please find a more suitable term than “gain”

Line 325: the term “led” should be changed

Line 327: one cannot assess “impact” from an observational study. Please use a more appropriate term

Line 331: please substitute the language that suggests this report can “provide a clinical framework for clinical decision-making”

Line 334: this opening statement isn’t qualified until the data from Boyer et al is considered, including its supplemental tables and figures

Line 341: please find a more scientific adjective than “best”

Line 343: please list the most important limitations of LCSG study which were the lack of PET and no requirements for whole-body CT staging

Line 350: as this is a limitations paragraph, a final disclaimer should be stated that these data are useful to inform future study design and should not be used to guide clinical decisions

Line 353: please use language that is more scientific than “the superior treatment”. Summarize what outcome measure demonstrated higher values.

Line 354: this final sentence needs to be modified to avoid making a clinical recommendation

Please review Welp et al in Sem Thor CV Surg 2020

Please review the limitations of the Bryant et al paper that was written about here: https://www.healio.com/news/hematology-oncology/20171228/surgery-extends-survival-in-earlystage-lung-cancer

Reviewer #2: This is a well-balanced and comprehensive retrospective analysis of lung cancer treatment and CAD in veterans. The concepts are highly impactful and timely. No major concerns are identified with the authors approach.

Reviewer #3: COMMENTS TO THE AUTHOR

This is an interesting and well-written study describing the application of simulation modeling to evaluate optimal treatment of Veteran patients with stage I NSCLC with COPD and/or CAD. Study findings indicated that lobectomy was optimal for patient under 70 regardless of comorbidity status. While in general there was no optimal treatment for those over 80, treatment varied according to CAD status. This is a very timely and unique approach to investigating ideal treatment for stage I NSCLC for which SBRT is evolving as a recommended treatment option in certain situation. These findings will be helpful in clinical decision-making for Veterans, which is a population that’s older and has more comorbidities than the general population. Comments for consideration are provided below:

1. The authors used evidence from several Veteran-specific and other data sources incorporate estimates into the model. More detail is needed to help the reader understand the study populations the estimates were derived from in order to put into context the similarities/differences of the various cohorts. For example, the LC and non-LC mortality was based on CDW cancer registry data of 14, 029 patients diagnosed 2000-2015 with stage I-IIIA NSCLC retaining those who had lobectomy. So the lobectomy cohort was among those with stage I-IIIA and not just stage I? For the VASQIP--VA cancer registry linkage, were the 6,022 patients from the same diagnosis period and stage? Similarly, for the SBRT cohort, was this from the same pts diagnosed 2000-2015? For the VACS, what was the time period of data collection, especially since this was a non-cancer cohort. Additional clarification would be helpful to better understand the source of model inputs and potential impact on results.

2. Was there any consideration or ability to incorporate CAD severity (eg number of obstructive coronary arteries or other scoring system), as done for COPD, rather than just a binary variable?

3. It’s not clear if/how race/ethnicity was factored in the analyses? It would be important for the authors to discuss this as curative therapy has been shown to vary by race/ethnicity as well as significant race/ethnic differences in the major comorbidities (CAD, COPD) of interest in this study.

4. Minor comment: on Table 3, I think the first column is incorrectly labeled as ‘size/histologic subtype’ since it includes the treatment complications.

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Reviewer #1: No

Reviewer #2: Yes: Farrah Kheradmand MD

Reviewer #3: No

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Optimal Treatment Strategies for Stage I Non-small Cell Lung Cancer in Veterans with Pulmonary and Cardiac Comorbidities

PONE-D-20-35238R1

Dear Dr. Sigel,

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,

Hyun-Sung Lee, M.D., Ph.D.

Academic Editor

PLOS ONE

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Reviewers' comments: