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Date: Jul 02, 2021 To: "Malavika Prabhu"
From: "The Green Journal" [email protected] Subject: Your Submission ONG-21-1117
RE: Manuscript Number ONG-21-1117
Universal Hepatitis B Antibody Screening and Vaccination in Pregnancy: A Cost Effectiveness Analysis Dear Dr. Prabhu:
Your manuscript has been reviewed by the Editorial Board and by special expert referees. Although it is judged not acceptable for publication in Obstetrics & Gynecology in its present form, we would be willing to give further consideration to a revised version.
If you wish to consider revising your manuscript, you will first need to study carefully the enclosed reports submitted by the referees and editors. Each point raised requires a response, by either revising your manuscript or making a clear and convincing argument as to why no revision is needed. To facilitate our review, we prefer that the cover letter include the comments made by the reviewers and the editor followed by your response. The revised manuscript should indicate the position of all changes made. We suggest that you use the "track changes" feature in your word processing software to do so (rather than strikethrough or underline formatting).
Please be sure to address the Editor comments (see "EDITOR COMMENTS" below) in your point-by-point response.
Your paper will be maintained in active status for 21 days from the date of this letter. If we have not heard from you by Jul 23, 2021, we will assume you wish to withdraw the manuscript from further consideration.
REVIEWER COMMENTS:
Reviewer #1:
I have reviewed the manuscript and have the following comments:
1. Although cost effective based on the assumptions put into the QALY assessment, it is still an increased cost to the system. How much will this cost to implement in the US per year?
2. The methods state that the analysis evaluated the outcomes, costs and cost effectiveness of universal screening to no screening and the results show a benefit. Did the analysis actually compare the ACOG recommendation for risk based screening for vaccine administration versus universal screening for immunity? If not, the second sentence in the discussion is not justified. Neither is the recommendation for implementing this strategy.
3. How cost effective is the current ACOG recommended strategy and what is its ICER per QALY?
Reviewer #2:
Prabhu et al performed a decision and cost effective analysis of universal screening for hepatitis B immunity and vaccination among all pregnant women in the United States.
Abstract: Authors provide a structured summary of objectives, methods, results, and conclusions.
Introduction: Authors do a good job of identifying and bounding the problem, and provide relevance for health policy and practice decisions (e.g. increasing susceptibility to HBV among reproductive aged women, the risks of hepatitis B in pregnancy and chronic hep B, and alternative course of action to screen and vaccinate during pregnancy).
Materials and Methods: 107-110 Design model is defined and depicted by convention in figure 1. Design model appears appropriate for identified problem in the decision analysis. 112-113, Table 1: Model parameters appear appropriate.
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Authors report a base case, and reference range for the parameters. Regarding costs, authors address societal costs (direct medical and non-medical and indirect costs) including health services, patient time, caregiver costs, and direct costs to partake in intervention.
Outcomes: 146-155 Outcome measures are clinically relevant and appear appropriate.
151 Total costs were derived from literature, and adjusted for contemporary analysis. 144-145 They use an appropriate time horizon based on prior studies and adjust costs based on inflation. Utilities are considered from a maternal perspective, which is appropriate. QALYs and ICER are defined, and appear appropriate. 171-172 Recommend authors justify choice of discounted rate.
Analysis: 183-194 Authors do a good job of defining sensitivity analyses that were used.
Results/Discussion:
Recommend authors discuss if productivity costs were used in the analysis and if not, explain why (e.g. QALY includes ability to be productive). If they were, suggest stating this more explicitly in the manuscript, and consider reporting analysis with and without these costs based on recommendations from the US Panel on Cost-Effectiveness Analysis (Gold et al 1996) as this may have a large effect on results.
Figures and Tables: Cost analysis and model input for costs, probabilities and relative risks are depicted in tables 1.
References: Appear appropriate for the manuscript.
Reviewer #3:
The cost-effectiveness analysis by Prabhu et al. is a well constructed argument for the financial impact of adding routine screening for Hepatitis B immunity (not just active Hepatitis B infection) to routine prenatal care as well as vaccinating those who are not immune. This represents an important paradigm shift that is focused on the health and wellbeing of the mother over the course of her lifetime, rather than simply focused on reducing vertical transmission to the fetus/neonate, which is the orientation of the recommendations surrounding hepatitis B infection screening. Thus, rather than using prenatal care as a time for screening in order to reduce harms to the fetus, the authors envision prenatal care as a time to capture & assess the health of a large proportion of women in the United States - including many women who may not otherwise engage with the health care system during their adult lives.
Traditionally, studies that use QALYs as the denominator are referred to as cost-utility studies rather than cost- effectiveness - while cost-effectiveness may be more acceptable/understandable to a more lay audience, it seems the more accurate categorization for this study would be a cost-utility study.
With all cost-effectiveness models, the merit of the authors' findings rests on the assumptions that are made, in particular, the assumptions made for probabilities, costs, and utilities. One limitation to the current manuscript is that many of the assumptions are generated from a very limited set of publications. If the data exists, Table 1 would benefit from additional references that support the assumptions made.
While the authors provide sensitivity analyses that assess the cost-effectiveness across a range of inputs, the discussion should include comparison to findings in the literature from other publications that examine similar topics, such as those suggested by Toy et al. (https://www.ncbi.nlm.nih.gov/books/NBK442231/).
The authors chose a WTP threshold of $100,000/QALY. While this threshold is frequently used in the literature as a standard, there are many studies that suggest a threshold of $50,000. It would be very interesting to see how the necessary frequencies of HBV immunity, HBV incidence, and vaccination acceptance change when a lower willingness to pay is utilized. All interventions have opportunity costs, and providing funding to universally screen for HBV immunity &
provide vaccination adds to overall dollars spent on healthcare as part of the GDP, and will result in loss of investment elsewhere.
Lastly, the authors do not provide any information about what proportion of the non-immune population is cared for by Medicaid as a payer versus private insurance. While the perspective of the manuscript is focused on the total cost to the healthcare system, it would be interesting to know which payers may be shouldering the primary burden of increased cost in order to implement this intervention.
Figure 5: The x-axis intervals need to be renumbered - as they all currently appear as zero.
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STATISTICS EDITOR COMMENTS:
Table 1: The range for transplant year one costs does not include the expected value. ? typo.
Table 2: Would be more informative if there were three scenarios, that is, include the proposed risk based screening to contrast with universal screening.
Fig 4: Need to round the costs on vertical axis to more realistic precision, e.g, to nearest whole dollar amount.
Fig 5: Need to include values for x-axis, since all are labelled = 0.
General: The model contrasts two unlikely scenarios: (1) no screening, no vaccination vs (2) universal screening, universal vaccination. It seems unlikely screening would be universal and that follow-up for > 1 vaccine administration would be 100%. Also, it seems likely that those events might be correlated to higher risk groups for Hep B (incarcerated women, drug addicts, other marginalized groups). So, the variables % screened and then % vaccinated should be a part of the model, rather than as a binary choice of all vs none.
lines 205-206: Should include the tornado analysis as a Table or figure.
Editor: Please as suggested by Reviewer #4 include a risk based strategy in your model. Also, for several of your inputs, please broaden the sensitivity analysis. For example, please include low levels of actual vaccination among others.
A broader issue: With no direct pregnancy benefit in your model, it seems like you are pushing a public health policy agenda not endorsed by, say, the CDC. That is, why pregnant women-just because they are in care? If you haven't, please discuss the implications of this "captive audience" screening and immunization approach.
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August 18, 2021
Re: ONG-21-1117
Dear Dr. Rouse,
Thank you for the opportunity to revise our manuscript. We appreciate your and the reviewers’
helpful comments to improve our manuscript for publication. We have made a number of revisions to the manuscript. Below please find our point by point response to each of the comments in bold, with line numbers where we have made changes. We have also read the Instructions for Authors and believe our manuscript is in agreement with the instructions.
We would like to address here the comments by you and several reviewers regarding including a third model that addresses a risk-based screening and vaccination approach – or the ACOG approach. This was challenging to model, as many of the risk factors of HBV do not have prevalences reported in the literature. However, there are some risk factors (IV drug use, HIV- seropositive, recent STI) that do have prevalences available. Using these data, we assumed that a fraction of our theoretical population was at the highest risk of HBV acquisition and thus would be recommended for vaccination. We removed this fraction of individuals from our theoretical cohort, updated the annual incidence based on exclusion of this high risk group, and repeated our analyses as described in the manuscript. With this approach, our recommendation for universal screening and vaccination remains cost effective, with an ICER of $2133 per QALY. These findings are now included in the manuscript. From a public health perspective, we know that risk-based screening recommendations often fall short of identifying the population in need. And finally, upon our re-reading of the ACOG Perinatal Guidelines, the guidelines
recommend directly vaccinating high risk individuals and not first screening them for immunity.
We do not believe that this would be an appropriate approach as some women would receive unindicated immunizations. For all of these reasons, we believe that our comparison of universal screening and vaccination vs no universal screening and no vaccination is
appropriate. However, if it would improve our work for publication, we would be happy to further describe this approach and compare universal screening and vaccination to an approach of vaccinating high risk women only.
We also would like to note that we presented this work in part at the Infectious Diseases Society of Obstetrics & Gynecology virtual meeting as an oral presentation on 7/30/2021. Marguerite Susich was the primary and presenting author.
We look forward to hearing from you and appreciate the opportunity to revise our work.
Sincerely,
Malavika Prabhu
REVIEWER COMMENTS:
Reviewer #1:
I have reviewed the manuscript and have the following comments:
1. Although cost effective based on the assumptions put into the QALY assessment, it is still an increased cost to the system. How much will this cost to implement in the US per year?
To implement the approach of universal screening and vaccination, the lifetime costs for the cohort are $18,226,088. This is listed in line 229.
2. The methods state that the analysis evaluated the outcomes, costs and cost effectiveness of universal screening to no screening and the results show a benefit. Did the analysis actually compare the ACOG recommendation for risk based screening for vaccine administration versus universal screening for immunity? If not, the second sentence in the discussion is not justified.
Neither is the recommendation for implementing this strategy.
Thank you for this comment. Per our reading of the ACOG Perinatal Guidelines, the recommendation is for vaccination of high risk individuals without first screening for immunity. We have revised our text in lines 98-100 and lines 308-311 to note this. The analytic approach we presented in the manuscript is a comparison of universal
screening and vaccination versus no universal screening and no vaccination. In order to account for the ACOG approach as best as possible, in our revised model, we removed those women that would be categorized as high risk for HBV vaccination from the theoretical cohort. Thus, the third model in the current paper is still universal screening versus no screening, but now only among pregnant persons that would be considered low risk. This updated model in the lower risk population is described in lines 208-216 and lines 241-247 and found that universal screening and vaccination remained a cost effective approach even among the lower risk population remaining. As our model does not compare against a risk based approach, we have removed reference to a risk based approach in the discussion (which is now the third sentence of the discussion - line 279- 283).
3. How cost effective is the current ACOG recommended strategy and what is its ICER per QALY?
We do not compare the ACOG strategy to no screening/no vaccination thus cannot provide this ICER per QALY. The ACOG strategy is not a screening strategy which is what we were analyzing. Further, we want to reinforce that when one considers only the low-risk patients, an approach of universal screening and vaccination among them as compared to no screening or vaccination is cost effective.
Reviewer #2:
Prabhu et al performed a decision and cost effective analysis of universal screening for hepatitis
B immunity and vaccination among all pregnant women in the United States.
Abstract: Authors provide a structured summary of objectives, methods, results, and conclusions.
Introduction: Authors do a good job of identifying and bounding the problem, and provide relevance for health policy and practice decisions (e.g. increasing susceptibility to HBV among reproductive aged women, the risks of hepatitis B in pregnancy and chronic hep B, and
alternative course of action to screen and vaccinate during pregnancy).
Materials and Methods: 107-110 Design model is defined and depicted by convention in figure 1. Design model appears appropriate for identified problem in the decision analysis. 112-113, Table 1: Model parameters appear appropriate. Authors report a base case, and reference range for the parameters. Regarding costs, authors address societal costs (direct medical and non-medical and indirect costs) including health services, patient time, caregiver costs, and direct costs to partake in intervention.
Outcomes: 146-155 Outcome measures are clinically relevant and appear appropriate.
151 Total costs were derived from literature, and adjusted for contemporary analysis. 144-145 They use an appropriate time horizon based on prior studies and adjust costs based on
inflation. Utilities are considered from a maternal perspective, which is appropriate. QALYs and ICER are defined, and appear appropriate.
171-172 Recommend authors justify choice of discounted rate.
Thank you for your comments above. We chose a discount rate of 3% as this is recommended by the Second Panel on Cost Effectiveness in Health and Medicine ( https://jamanetwork.com/journals/jama/fullarticle/2552214).
Analysis: 183-194 Authors do a good job of defining sensitivity analyses that were used.
Thank you for this comment.
Results/Discussion:
Recommend authors discuss if productivity costs were used in the analysis and if not, explain why (e.g. QALY includes ability to be productive). If they were, suggest stating this more explicitly in the manuscript, and consider reporting analysis with and without these costs based on recommendations from the US Panel on Cost-Effectiveness Analysis (Gold et al 1996) as this may have a large effect on results.
Thank you for this comment. Productivity costs were not directly included in this
analysis, but are at least in part indirectly included in the QALY estimates. Not including these costs results in a conservative approach to the cost effectiveness analysis,
because avoiding the loss of productivity with increased health would only result in increased costs in the baseline approach and a lower ICER. In addition, the downstream conditions are not very common, so would not significantly change the overall analysis.
However, we would be happy to incorporate these costs if the Editors feel this would improve our work for publication.
Figures and Tables: Cost analysis and model input for costs, probabilities and relative risks are
depicted in tables 1.
References: Appear appropriate for the manuscript.
Reviewer #3:
The cost-effectiveness analysis by Prabhu et al. is a well constructed argument for the financial impact of adding routine screening for Hepatitis B immunity (not just active Hepatitis B infection) to routine prenatal care as well as vaccinating those who are not immune. This represents an important paradigm shift that is focused on the health and wellbeing of the mother over the course of her lifetime, rather than simply focused on reducing vertical transmission to the
fetus/neonate, which is the orientation of the recommendations surrounding hepatitis B infection screening. Thus, rather than using prenatal care as a time for screening in order to reduce harms to the fetus, the authors envision prenatal care as a time to capture & assess the health of a large proportion of women in the United States - including many women who may not otherwise engage with the health care system during their adult lives.
Traditionally, studies that use QALYs as the denominator are referred to as cost-utility studies rather than cost-effectiveness - while cost-effectiveness may be more
acceptable/understandable to a more lay audience, it seems the more accurate categorization for this study would be a cost-utility study.
Thank you for this comment. We agree that the analysis we present is consistent with a cost utility study. Cost-effectiveness analyses include any with costs in the numerator and some measure of clinical outcomes in the denominator. The cost-utility analysis is a subgroup of cost-effectiveness analyses and generally considered the best to be
compared between a variety of clinical situations. We believe many readers may be more familiar with the terminology cost effectiveness analysis and thus would like the title to remain as is, but would be happy to change the title if the Editors also prefer a title change.
With all cost-effectiveness models, the merit of the authors' findings rests on the assumptions that are made, in particular, the assumptions made for probabilities, costs, and utilities. One limitation to the current manuscript is that many of the assumptions are generated from a very limited set of publications. If the data exists, Table 1 would benefit from additional references that support the assumptions made.
An additional literature search was conducted to broaden the inputs denoted in Table 1.
We have now broadened the references for multiple inputs. These additional references supported the assumptions made for probabilities and ranges in the model.
While the authors provide sensitivity analyses that assess the cost-effectiveness across a range of inputs, the discussion should include comparison to findings in the literature from other publications that examine similar topics, such as those suggested by Toy et al.
The Toy et al article is a CEA aimed at diagnosis and treatment of chronic hepatitis B to
avoid the complications such a cirrhosis, cancer, death, in non-pregnant individuals. Our
manuscript addresses screening for susceptibility to hepatitis B and vaccinating
susceptible individuals in pregnancy. We are unable to identify other publications on the cost effectiveness of screening for an infection and vaccinating during pregnancy. The closest parallel is screening for Hepatitis C infection, with linkage to care and
postpartum treatment, which is a cost effective intervention. We draw a parallel between Hep B screening and vaccination to hepatitis C screening and linkage to care in lines 296-307.
The authors chose a WTP threshold of $100,000/QALY. While this threshold is frequently used in the literature as a standard, there are many studies that suggest a threshold of $50,000. It would be very interesting to see how the necessary frequencies of HBV immunity, HBV incidence, and vaccination acceptance change when a lower willingness to pay is utilized. All interventions have opportunity costs, and providing funding to universally screen for HBV immunity & provide vaccination adds to overall dollars spent on healthcare as part of the GDP, and will result in loss of investment elsewhere.
We have changed our willingness to pay threshold to $50,000, in order to chose a conservative threshold for the evaluation of this intervention, and note this in lines 191- 193. The impact of this change is as follows: universal screening remains the cost-
effective intervention until HBV immunity in the population reached 98.2% and as long as the annual incidence of HBV is above 0.00013%. This is demonstrated in Figures 2, 3, and 4.
Lastly, the authors do not provide any information about what proportion of the non-immune population is cared for by Medicaid as a payer versus private insurance. While the perspective of the manuscript is focused on the total cost to the healthcare system, it would be interesting to know which payers may be shouldering the primary burden of increased cost in order to
implement this intervention.
The fraction of annual births paid for by Medicaid is 42.1%, according to the latest data from 2019 births (https://www.cdc.gov/nchs/data/databriefs/db387-H.pdf). We may be able to assume that approximately 42% of the national costs of screening may be borne by Medicaid. However, the fraction of the national costs of immunizing susceptible women is not known, as we do not have any data from the literature upon which to base this calculation. We address this limitation in lines 340-343.
Figure 5: The x-axis intervals need to be renumbered - as they all currently appear as zero.
Thank you. We have renumbered the x-axis.
STATISTICS EDITOR COMMENTS:
Table 1: The range for transplant year one costs does not include the expected value. ? typo.
Thank you for pointing this out. We have now updated Table 1 with the correct transplant
cost range in year 1.
Table 2: Would be more informative if there were three scenarios, that is, include the proposed risk based screening to contrast with universal screening.
Including a third arm to mirror the ACOG approach, which advocates for vaccination for high risk groups without first screening for immunity, has drawbacks. First, many of the risk factors for HBV do not have prevalences reported in the literature, which would lead to significant assumptions underpinning the model. Second, from a public health
perspective, we know that risk-based screening recommendations often fall short of identifying the population in need, and can often be associated with implicit or
unconscious bias. Finally, we don’t agree with proceeding to vaccination without first screening for immunity, as some women would receive unindicated vaccinations during pregnancy. For all of these reasons, we believe comparing our approach to one of no screening and vaccination is appropriate. However, we did include an additional sensitivity analysis in which we removed the highest risk women who would be most likely to benefit from screening and vaccination. Even after removing this group, our approach of universal screening and vaccination remains cost effective. This suggests that our model is not only benefiting the highest risk women but rather is cost effective on a population level. We have included this explanation in lines 208-216 and lines 241- 247. We would be happy to work further with the Editors on expanding the presentation of this analysis if this would improve our work for publication.
Fig 4: Need to round the costs on vertical axis to more realistic precision, e.g., to nearest whole dollar amount.
We have updated the y-axis to whole numbers.
Fig 5: Need to include values for x-axis, since all are labelled = 0.
We have updated the x-axis with the correct labels.
General: The model contrasts two unlikely scenarios: (1) no screening, no vaccination vs (2) universal screening, universal vaccination. It seems unlikely screening would be universal and that follow-up for > 1 vaccine administration would be 100%. Also, it seems likely that those events might be correlated to higher risk groups for Hep B (incarcerated women, drug addicts, other marginalized groups). So, the variables % screened and then % vaccinated should be a part of the model, rather than as a binary choice of all vs none.
Thank you for this comment and for helping us to clearly communicate our assumptions for the reader. While our strategy is named universal screening and universal
vaccination, as that would be the policy recommendation, the following numerical inputs
were used to estimate the screening rate (84%) and vaccination rate across all 3 vaccines
(61%). These assumptions are noted on line 120 and line 133. The screening rate for
HbsAg is 84%; we assumed a similar screening rate for HbsAb. The vaccination rate of
61% was based off the MMWR from 2020 that reports influenza vaccination coverage and
was varied from 55 to 67% in the one-way sensitivity analysis. Figure 4 demonstrates that as long as vaccination rate in pregnancy is more than 2.6%, this approach is cost
effective. We also address this now in the discussion in lines 321-331 to clarify this point for the reader.
lines 205-206: Should include the tornado analysis as a Table or figure.
The tornado analysis is now included as Figure 1.
Editor: Please as suggested by Reviewer #4 include a risk based strategy in your model. Also, for several of your inputs, please broaden the sensitivity analysis. For example, please include low levels of actual vaccination among others.
Thank you for these comments. As above, we have addressed the risk-based strategy by removing high risk women from the theoretical cohort and repeating the analysis as above with 2 arms – universal screening and vaccination (where the assumption is not 100% screening nor 100% vaccination) versus no universal screening and no
vaccination. Removing these women makes our theoretical cohort low-risk and thus further tests our approach. Our findings demonstrate that universal screening and vaccination remains cost effective. This is described in lines 208-216 and lines 241-247.
We have further broadened our sensitivity analysis to include the above, as well as decreased our willingness to pay threshold to a conservative estimate of $50,000. We also increased the number of references to inform our probabilities, costs, and utilities.
We feel these changes have tested our model to ensure that our proposed approach remains cost effective. We would be happy to work with the Editors to further broaden our sensitivity analyses if this is desired.
A broader issue: With no direct pregnancy benefit in your model, it seems like you are pushing a public health policy agenda not endorsed by, say, the CDC. That is, why pregnant women-just because they are in care? If you haven't, please discuss the implications of this "captive audience" screening and immunization approach.
This is a good point and we hope that this work does get attention from the CDC and
other public health organizations. We specifically address this point in lines 296-307.
EDITORIAL OFFICE COMMENTS:
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abstract word count: 275
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We have updated our manuscript accordingly.
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In addition, the American College of Obstetricians and Gynecologists' (ACOG) documents are frequently updated. These documents may be withdrawn and replaced with newer, revised versions. If you cite ACOG documents in your manuscript, be sure the references you are citing are still current and available. Check the Clinical Guidance page
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If the reference you are citing has been updated and replaced by a newer version, please ensure that the new version supports whatever statement you are making in your manuscript and then update your reference list accordingly (exceptions could include manuscripts that address items of historical interest). If the reference you are citing has been withdrawn with no clear replacement, please contact the editorial office for assistance ([email protected]).
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We have uploaded each figure as its own file.
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Sincerely,
Dwight J. Rouse, MD Editor-in-Chief
2020 IMPACT FACTOR: 7.661
2020 IMPACT FACTOR RANKING: 3rd out of 83 ob/gyn journals
