NWX HHS FDA (US)

Moderator: Irene Aihie

08-25-2014/2:00 pm CT

Confirmation # 8306676

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NWX HHS FDA (US)

Moderator: Irene Aihie

August 25, 2014

2:00 pm CT

Coordinator: Welcome and thank you for standing by. At this time, all participants are in a

listen-only mode until the question and answer session of today's call. At that

time, if you would like to ask a question, you may do so by pressing Star 1.

Today's conference is being recorded. If you have any objections, please

disconnect at this time. I now would like to turn the meeting over to (Tammy

Worth). You may begin.

(Tammy Wirt): Hello and welcome to today's FDA webinar. I'm (Tammy Wirt), the acting

branch chief for CDRH Strategic Communication Branch in the Office of

Communication and Education.

Today we will be discussing the final guidance document, a valuation of

specific data and medical device clinical studies which was released with the

FDASIA section 907 action plan on August 20, 2014. The final guidance

outlines specific recommendations for considering sex and other variables

during the study design stage to improve consistency of analysis and reporting

of information on demographics in labeling and other documents.
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Today, (Jismi Johnson) from CDRH's Office of Device Evaluation will

provide an overview of the guidance including what has changed from draft to

final and will answer any questions following the presentation.

Also with us today to assist with the Q&A portion of our webinar, our subject

matter experts from the Office of the Center Director and the Office of

Surveillance and Biometrics. Following the webinar, the slide presentation,

audio recording and written transcripts of today's program will be available on

the CDRH learn section of the FDA website. Now I give you (Jismi).

(Jismi Johnson): Good afternoon welcome. My name is (Jismi Johnson) and I'm a reviewer in

the Office of Device Evaluation within Center for Devices and Radiological

Health. Today we will review the final guidance for industry and FDA staff,

evaluation of site specific data and medical device clinical studies which was

posted on our website August 20, 2014.

Our presentation today will go over the objectives, scope and background of

the guidance followed by a summary of the major comments received on the

draft guidance and the major revisions made to the guidance in response. Then

we'll provide a brief summary of the guidance content including a decision

framework for staff and industry to use. We'll open it up for a question and

answer session at the end of the presentation.

This guidance document provides recommendations on the study and

evaluation of set specific data and medical device clinical studies. It outlines

the Center for Devices and Center for Biologics expectations regarding set

specific patient enrollment, data analysis and reporting of device study

information. The guidance is intended to improve the quality and consistency

of available data regarding the performance of medical devices in both sexes 

by encouraging appropriate enrollment by sex in device clinical studies and
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appropriate interpretation and assessment if the data from such studies are

analyzed by sex. We acknowledge that the evaluation of sex specific data in

medical device clinical studies benefit patients, their medical providers as well

as clinical researchers and others.

The specific objectives of this guidance are to encourage the consideration of

sex and associated covariates during the study design stage, to provide

recommendations for study design and conduct to encourage appropriate

enrollment of each sex, to outline recommended sex specific statistical

analyses of study data with the framework for considering sex specific data

when interpreting overall study outcomes and finally, to specify FDA's

expectations for reporting sex specific information and summaries in labeling

for approved or cleared medical devices.

Prior to developing the policy set forth in this guidance, CDRH publicly

sought input from a variety of experts and stakeholders regarding the study

and evaluation of women in clinical studies for medical devices. This

guidance document reflects the recommendation generated in these public

workshops and subsequent internal agency discussions. The scope of the

guidance clarifies that this document focuses on sex, that the

recommendations can be used for enrollment in data analysis by other

demographic variables including age, race and ethnicity.

Additionally, we acknowledge that the recommendation for evaluating the

impact of the sex demographic variable may not be applicable for all devices.

Such cases include certain obstetric gynecological and urologic devices that

are intended for single sex or for in vitro diagnostic device clinical studies that

you use to identify leftover specimens in which demographic information may

not accompany the samples.
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We received comments from 17 external stakeholders on the draft guidance.

Many comments applied to the statistical section. These included an overall

clarification on statistical concepts described as well as comments on when

studies should be powered to look for sex difference. When additional data

would be needed? Comments on first conducting primary effectiveness

analyses and then subgroup analyses and poolability. FDA carefully reviewed

all of the comments and modified the draft guidance document to address

those.

In response to the comments, the statistics section entitled Considering Sex in

Study Design and Data Interpretation was revised to provide more clarity. As

we will go into later in the presentation, this section of the guidance was

updated to discuss statistical concepts, to set the stage for statistical analyses

for sex specific differences, include recommendations for sex specific

statistical elements to consider when designing a clinical study, include

recommendations for analyzing data from one arm in comparative studies,

include recommendations for special considerations to take into account for

diagnostic devices and include recommendations for interpreting sex specific

data.

This section of the guidance we think addresses the major comments received.

It discusses when additional data are needed which was a repeated comment

in the docket. If any clinically meaningful sex difference are found, we

recommend discussion with FDA on whether additional data are needed to

address any remaining sex specific questions.

When clinically meaningful differences between sex are observed in safety or

effectiveness, additional data may be required. This section also discusses

situations where there's insufficient data to determine if sex is associated with

differences.
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This guidance document defines sex and gender for the Institute of Medicine

2001 Consensus Report. Sex refers to the classification of things generally as

male or female according to their reproductive organs and functions assigned

by chromosomal complement. Gender refers to a person's representation as

male or female or how that person is responded to by social institutions based

on the individual's gender presentation. Gender is rooted in biology and

shaped by environment and experience. For the purposes of this guidance

document, we use the term sex with the understanding that for most medical

device studies, gender is used as a surrogate for sex.

Certain medical products elicit different responses in women compared to

men. Differences may be attributable to intrinsic of extrinsic factors or

interactions between these factors. Covariates associated with female sex such

as size, age, comorbidity may be responsible for certain differences in safety,

effectiveness or design attributes such as failure mode. The final guidance

now provides three examples of where sex differences in a device clinical

study impacted FDA's regulatory considerations.

In the first example, a clinical study of a next generation ventricular assist

device showed that in subjects treated with investigational device, female sex

or covariates associated with sex -- such as body surface area -- were found to

be correlated with a higher rate of stroke in women as compared to men.

There were also trends towards increased rates of bleeding and infection in

women compared to men. For this product, the FDA Advisory Committee

recommended that a post approval study be conducted which would include

adequate collection of data regarding both sex and body surface area to

determine if differences exist in device performance.
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In another example related to cardiac resynchronization therapy defibrillators

or CRT-D, the benefit of CRT-D therapy over implantable cardio defibrillator

alone was observed to be greater in women than men. Since the sex specific

analysis was post hoc, the findings were considered exploratory. In this case,

the FDA Advisory Committee recommended that two post approval studies be

conducted that would include adequate collection of data regarding the effects

of the therapy in patients fulfilling the approved indication.

The metal on metal hip example was added to the final guidance. In June

2012, the orthopedic and rehabilitation devices advisory panel met to discuss

the clinical performance of metal on metal hip implants as well as associated

adverse events. The total hip replacement and hip resurfacing studies that

identified revision rates by sex showed that the revision rate appeared higher

among women three to five years post implantation in most studies.

From the panel deliberations, FDA issued a safety communication on metal on

metal hip implants including a recommendation for orthopedic surgeons that

women may be at risk for increased device wear and/or adverse local tissue

reactions and should be followed more closely.

Historically, women have been under represented or excluded from many

clinical studies. This has lead to a lack of information available for women

and their physicians regarding the risks and benefits of many medical

treatments and diagnostic procedures. The lack of available data for women as

illustrated by this summary timeline that highlights policy in various reports

issued over the years starting with the exclusion of women of childbearing

potential from drug studies in the 1970's to an FDA report to congress

published in 2013 that showed participation rates for women varied widely by

device product area.
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The lack of available data is also impacted by barriers to enrollment of women

in clinical studies. There are numerous reasons for lower participation rates of

women. Some of the key reasons identified by participants at the 2008

workshop include a lack of understanding about the main obstacles to

participation of women in clinical research, inclusion/exclusion criteria that

may not be necessary and may unintentionally exclude women, a lack of

understanding about differences in disease etiology and pathophysiology that

may lead to under diagnosis and under referral of women, device

manufacturing limitations to accommodate anatomical differences between

women and men among other reasons.

It remains important that clinical trials include diverse populations which

reflect the intended population whenever possible and appropriate. In general,

to achieve an unbiased estimate of treatment effect in the overall population,

sponsors should plan to enroll representative proportions of women and men.

However, in cases where there be science or prior clinical study results

suggest treatment affect in only sex, sponsors may need to intentionally enroll

sufficient numbers to support a valid analysis, for example, for sex specific

claims.

We recommend that sponsors investigate whether sex differences may or may

not exist for the disease or condition which our device is intended to treat or

diagnose. The guidance provides approaches to increase enrollment of women

in a clinical study. These include, for example, targeting clinical sites where

recruitment of women is more easily facilitated, considering revision to the

enrollment criteria when appropriate or considering parallel cohorts for

collecting data on devices in women and investigating reasons for under

enrollment or non enrollment of women. This approach can also be applied to

other key demographic groups.
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The guidance provides enrollment recommendations for various stages of

clinical study design including new or ongoing studies, completed studies and

post market studies. The guidance also provides recommendations for

sponsors and investigators to help avoid or minimize loss to follow-up

regardless of sex.

The next section of the guidance, Section 5, discusses considering sex in study

design and data interpretation. We received more comments by stakeholders

on this section. As such, to add clarification of the concepts and clearly

distinguish the recommendations for the design stage versus analysis of data,

this section was revised the most. Unless the investigational device is intended

for use in only one sex, it is important that the variation in data across sex be

considered in both study design and interpretation of study data.

In this section of the guidance, we introduce statistical concepts for assessing

heterogeneity across sex groups. Here, heterogeneity refers to a difference and

outcome across sexes. The first subsection identifies and defines statistical

terms and tasks related to sex specific statistical analyses to ensure a mutual

understanding of the concepts before diving into the recommendations. After

introducing the concepts, general recommendations are provided for new or

ongoing studies, completed studies and for post marketing studies.

The next sub section provides recommendations to consider for the study

design stage. These include recommendations when sex group differences are

anticipated, pre specifying assessment of heterogeneity across sex groups in

study design, additional considerations for designing one arm and comparative

studies and study design considerations for diagnostic devices. As a note to

keep in mind, these concepts and recommendations are also captured in the

first decision framework on Page 24 of the guidance. The decision framework

will be discussed in further detail in a few slides.
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The next subsection, called Section 5, describes the recommendations for

analysis and interpretation of sex specific data in completed studies. Here we

outline recommendations for reporting the analysis of clinically meaningful

sex differences.

In general, all studies should report descriptive statistics for outcomes of

interest by sex. This analysis should examine data for clinically meaningful

sex differences and the primary effectiveness and safety endpoints as well as

key secondary endpoints at the primary follow-up time point regardless of the

potentially limited statistical power of these sex specific subgroup analyses.

We also delineate additional considerations for data analysis, for one arm

studies and comparative studies and finally, Section 5 of the guidance includes

a subsection on the interpretation of sex specific data. In this section, we

recommend discussing with FDA whether additional data are needed to

address any remaining sex specific questions if any clinically meaningful sex

differences are found.

If the results of your analysis suggests that there's insufficient data to assess

whether sex is associated with differences and outcomes, FDA may determine

that clinical data from additional subjects in one or both sexes may be needed

pre or post market to address potential sex specific questions related to safety

or effectiveness.

Although expected to be rare, in cases where clinically meaningful differences

between the sexes are observed in safety or effectiveness, FDA may request

additional confirmatory studies in one or both sexes, implement specific pre or

post approval study conditions and/or modify the design of subsequent

studies.
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We also acknowledge that there are limitations to interpreting clinically

meaningful differences in small data sets. As previously mentioned, these

recommendations are pictorially represented by the decision framework at the

end of the guidance which we will discuss in further detail.

Although sponsors may be the most interested in the generalizability of the

findings, individual patients and their medical providers may benefit from

more data regarding effectiveness and potential adverse events associated with

device use in a particular demographic subgroup. In Section 6 of the guidance,

we recommend that you report the number and proportion of subjects by sex

who are treated or diagnosed with your device as part of a clinical study. This

includes reporting enrollment of demographics, baseline characteristics and

comorbidities. The guidance provides example language for sponsors to

consider and use when reporting this information in the public documents.

Information regarding sex specific outcomes analyses should be described in

the labeling and review summaries regardless of whether the analyses are pre

specified or post hoc. Covariates that might explain possible outcome

differences between sexes should also be described. If outcome differences by

sex are statistically significant and clinically meaningful, then the result of the

outcome analyses should be reported.

If the result of these analyses suggest a sex different in an endpoint or event

that is clinically meaningful but statistical significance is not reached,

sponsors should report the findings descriptively. If the results of these

analyses suggest no sex differences in outcomes, sponsors should report

which analyses were conducted and that no differences were found.
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As mentioned previously, many commenters were concerned that the

guidance recommendations applied to each and every clinical study and

wanted clarification on when additional data would be needed, when certain

recommendations apply and to which studies. Some commenters also

recommended a decision framework to provide guidance in these situations.

We took that into consideration and AdvaMed provided additional input and

suggested content to consider for a decision framework for industry and FDA

staff to use.

We work internally with our statistical colleagues to come up with a decision

tree for the study design phase as well as decision trees for analyses upon

completion of the clinical studies. The decision trees that we will discuss in

the next few slides are a pictorial representation of the recommendations

described in the tasks of Section 5 of the guidance document which discusses

the statistical consideration of study design and analysis.

The first decision tree provides recommendations to consider at the design

stage. This framework starts off asking whether the product used is intended

for single sex or both sexes. If it is limited to one sex, then no separate sex

analyses would be required. If the device will be used in both sexes, you

would move down the flow chart to recommendations to consider for all

clinical studies.

The recommendations for all clinical studies include pre specifying reporting

by sex, providing a strategy to recruit appropriate representation of women

which would ideally match the disease prevalence by sex, and reporting other

information including previous studies and disease science suggest a clinical

meaningful difference by sex. Regardless of the type of study design you use -

- single arm or comparative studies -- we believe that these recommendations

would apply to all clinical studies. After that recommendation box, the flow
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chart breaks down recommendations by type of clinical study: one arm study

and comparative study.

For a one arm study, you would follow all of the recommendations proposed

previously for all clinical studies and then also provide a strategy for assessing

heterogeneity. For a one arm study, you may also consider sex specific

objective performance criteria or a performance goal which would be

applicable when sex subgroup differences are anticipated.

An objective performance criteria or OPC refers to a numerical target value

derived from historical data from clinical studies and/or registries. For

example, developed via meta-analytic review of multiple clinical studies on

similar devices with sufficiently mature technology. A performance goal, or

PG, refers to a numerical value generated by data which may not be as robust

as those used to develop an OPC. Generally, the device technology is not as

well developed or mature for use of the PG as for an OPC.

Then we move onto the statistical design recommendations for a comparative

study. For comparative studies which covers non randomized controlled and

randomized controlled clinical trials, you would, again, follow the

recommendations for all clinical studies, control the overall type 1 error rate

of seeking multiple claims, pre specify interaction testing and consider

powering for sex specific claims when sex subgroup differences are

anticipated. For randomized controlled clinical trials, you may consider sex as

a stratification variable in the randomization process when appropriate and

when sex subgroup differences are anticipated.

The next two decision frameworks apply to the analysis stage of completed

clinical studies with recommendations for one arm and comparative studies.

For one arm studies including OPC, PG and observational studies, the
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decision framework starts with the initial question of is the overall treatment

affect statistically significant and clinically meaningful? If not, then this

would suggest that the analysis raises questions about whether the data can

support our marketing application. It is also recommended that subgroup

analyses not be conducted if the overall treatment affect is not statistically

significant and clinically meaningful.

If the overall treatment effect is statistically significant and clinically

meaningful, then you would continue down the flow chart to the next few

decision points.

The next decision point asks that you determine whether there's a significant

difference between sexes. If there is not then the data may be poolable across

sex. If there is a significant difference between sexes, then the next decision

points asks, is the sex difference clinically meaningful or statistically

significant after adjusting for other covariates? If not, the data may be

poolable across sex. If the sex difference is clinically meaningful and

statistically significant after adjustment for covariates, then the data may not

be poolable cross sex, analyses should be conducted separately and additional

data may be required.

We also acknowledge that there will be gray areas for some clinical study

results and marketing submissions. Therefore, in these situations where the

sex difference could not be statistically significant but not clinically

meaningful or clinically meaningful but not statistically significant, discussion

with FDA is advised.

Similar to the decision framework for a one arm study, a decision framework

was also created for comparative studies. For comparative studies, the

framework asks the same initial question of is the overall treatment affect
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statistically significant and clinically meaningful? If not, then this would

suggest that the analysis raises questions about whether the data can support a

marketing application and in this situation, subgroup analyses are not

recommended if the overall treatment affect is not statistically significant and

clinically meaningful.

If the overall treatment effective is statistically significant and clinically

meaningful, then you would continue down the flow chart. The next decision

point asks you to determine whether there's a significant interaction effect

between sex and the treatment and group for the outcome of interest. If there

is not, then the data may be poolable across sex.

If there is a significant interaction affect, the next decision point asks, is the

interaction affect clinically meaningful and statistically significant after

adjusting for other covariates? If not, the data may be poolable across sex.

If the interaction effect is clinically meaningful and statistically significant

after adjustment for covariates, then the data may not be poolable across sex,

analyses should be conducted separately and additional data may be required.

For comparative studies, your analyses and submission should also describe

the qualitative or quantitative nature of the interaction and clinical

significance of any differences. It is also acknowledge that other subgroup

analysis may be needed.

Not every clinical study will be black and white in terms of sex specific data.

Therefore, we advise you to discuss with FDA in situations where the sex

difference could be statistically significant but not clinically meaningful or

vice versa. This ends our formal presentation and now we'll take questions.
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Coordinator: Thank you. We will now begin the question and answer session of today's

conference. If you would like to ask a question, please do so by pressing Star

1, record your first and last name clearly when prompted. Once again, if you

would like to ask a question at this time, please press Star 1. Again, if you

would like to ask a question at this time, you may do so by pressing Star 1.

One moment please for our first question. Our first question comes from

(Ronnie). (Ronnie), your line is now open.

(Ronnie): Thank you. I was wondering if the FDA is now requiring sponsors to go back

to those studies that are completed and do the statistical analysis based on

gender?

(Jismi Johnson): Thank you for the question. For completed studies, we do want you to - we

recommend looking and conducting those analyses. The guidance does

provide recommendations for the different stages for new studies or ongoing

completed studies and studies that are at the post market stage.

Coordinator: Again, if you would like to ask a question, you may do so by pressing Star 1.

One moment please. Our next question comes from (Satish Roman). (Satish),

your line is open.

(Satish Roman): Hello. Can you hear me?

(Jismi Johnson): Yes.

(Satish Roman): So the guidance has been written for the analysis of overall (unintelligible)

affect being statistically significant without consideration for a non

(unintelligible) trials. What about non inferiority trials? What analyses are

required for such trials?
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(Lilly Yue): Good question. Thank you. This is Lilly Yue. I would say that's the same for

either a superiority study or a non inferiority study.

(Satish Roman): I'm sorry. I couldn't follow you clearly.

(Lilly Yue) Okay. The requirement is the same for either a superiority study or a noninferiority study.

(Satish Roman): Okay. Thanks.

Coordinator: Our next question comes from (Susan Campbell). (Susan), your line is now

open.

(Susan Campbell):Yes. Thank you. I just wanted to clarify. On the sex specific analysis, I believe

you said that reporting must be done regardless of power and so I'm just

wondering how a sponsor could say that there were not enough women in the

trial and therefore, the analysis can't be done and what is FDA going to do in

that case?

(Jismi Johnson): Thank you for the question. Dr. Lilly Yue will be answering that.

:

Lilly Yue: That is a good question. Usually, we calculate power, study power, based on, 

for example, the treatment difference for primary effectiveness or safety 

endpoint. We may not have sufficient power for testing sex difference. But, 

no matter what, we do need to report study results by sex. 

(Jismi Johnson): For future questions, if everyone could identify their affiliation when

announcing their name, we would appreciate that. Thank you.
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Coordinator: As a reminder, if you would like to ask a question at this time, please press

Star 1, record your first and last name along with your affiliation. There

appears to be no further questions in queue at this time.

(Tammy Wirt): Okay. Thank you. This is (Tammy Wirt). Thank you for your questions today.

If you have additional questions, please submit them to dice@fda.hhs.gov.

Please remember that this presentation - I'm sorry. Two more questions just

came in.

Coordinator: One moment please. Our next question comes from (Jessica). I'm sorry

(Jessica). I'm going to have you to announce your affiliation. It was a little

difficult to make out but (Jessica), your line is now open.

(Jessica): Yes. (Jessica) with (Roche) and our question is regarding transgender. We've

had studies where people have identified themselves as transgender and are

taking hormones to either be more male and/or more female like. How should

the sponsor handle that when we run into situations like that?

(Jismi Johnson): Thank you for your comment and question. We did get this comment also to

the docket and we understand that there will be unique considerations for this

group and we do have different forums that are looking into this. For example,

the health and women program but I think this would need to be handled on a

case by case basis during the pre submission phase or the early study design

stage. Does that answer your question?

(Jessica): No. I mean, because we're not going to know that in the early design stage.

You would find that out when you're recruiting your subjects and all of a

sudden you have one that tells you, by the way, I'm born male but now I'm

female.
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(Jismi Johnson): I don't have a good answer for you for this specific situation. I think when we

get those situations, there will be a little bit more discussion just because at

this moment, we haven't had that specific situation I think. We will continue

to discuss and hopefully have an answer when that situation actually does

arise.

(Jessica): Thank you.

(Jismi Johnson): Sure.

Coordinator: Our next question comes from (Beta) with Pita Medical. (Beta), your line is

now open.

(Beta): Thank you. I'm just actually calling to find out if this adversely affects the

510K submission? We've already submitted our 510K application and I want

to know whether or not we'd have to do any further follow-up on old studies

that we use to supplement this application for sex specific data.

(Jismi Johnson): I think for that specific submission you should contact FDA and there will be

discussion between the review division, the statistics folks on your specific

situation.

(Beta): Okay.

(Jismi Johnson): Thank you.

Coordinator: Our next question comes from (Tonya Desenza) with (unintelligible). Your

line is now open (Tonya).
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(Tonya): Yes. Hello. We asked a question in the chat. It was just a technical question to

know the name of the presenter. We hadn't caught that. I'm sorry.

(Jismi Johnson): (Jismi Johnson), Biomedical Engineer in Office of Device Evaluation.

(Tonya): (Jismi Johnson)?

(Jismi Johnson): (Jismi) yes. J-I-S-M-I, last name (Johnson).

(Tonya): Thank you very much.

Coordinator: As a reminder, if you would like to ask a question, please press Star 1, record

your first and last name clearly along with your affiliation when prompted.

(Tammy Worth): Okay. If there are no more questions, again, thank you for attending today's

webinar and for your questions. If you have additional questions, again, you

can submit them to dice@fda.hhs.gov and someone will get back to you

promptly. This presentation will be available on the CDHR learn section of

fda.gov. The written transcript and recording may take a couple of days to be

posted but should be posted no later than Friday, August 29. If you have

further questions, you can also use the contact information provided at the end

of this slide. As always, we appreciate your feedback on today's presentation,

thank you for participating and this concludes today's webinar.

Coordinator: Once again, this now concludes today's conference. All lines may disconnect

at this time.

END