Posts Tagged FDA

21st Century Cures and Off-Label Promotion Benefit HEOR and Drug Safety

Jim Davis

By Jim Davis

As my writing for the AdverseEvents Blog can attest, I’m in favor of data transparency. In my view, no organization should have monopolistic control over important information that limits the ability for healthcare decision makers to perform unbiased, objective comparative effectiveness research (CER). Furthermore, transparency leads to data and information being exchanged more freely, which will lead to an overall benefit to drug safety.

Pharmaceutical companies have historically had a bad reputation when it comes to transparency. In a large study conducted in 2004, of over 100 clinical trials, 65% of harms and outcomes were incompletely reported. However, in the past couple of years there has been a marked transformation by pharmaceutical companies to be completely transparent in publishing the results of all research conducted. Just searching Google for “pharmaceutical company transparency”, page one results show the public transparency policies of major manufacturers such as Janssen, UCB, and Takeda. This movement shows no signs of stopping and I believe it will be the rule, rather than the exception in short time.

It is now time for FDA to lift the remaining obstacles to transparency they have put in pharma’s way. And several ongoing initiatives may do just that.

The 21st Century Cures legislation attempts to provide a clear picture of what manufacturers can, and cannot, communicate with healthcare decision makers. New research from Avalere Health suggest that if approved, this could result in better evidence on cost-effectiveness, comparative benefit, and real-world outcomes for payers determining patient access to these medications. In addition to 21st Century Cures, on May 7 2015 Amarin Corporation, Plc filed a lawsuit against FDA, looking to lift restrictions  on marketing products based on claims that are currently not on a drug’s FDA approved label.

Pharmaceutical companies are the chief sponsor for most late stage and post-marketing drug research and they have the most to gain, and more importantly, lose, if their data fails to meet healthcare decision maker and market demands. Even though payers are demanding more real world data studies and health economics and outcomes research (HEOR), only 43% of respondents from a recent EY survey, agreed with the statement that “pharmaceutical companies have data that is credible for measuring and improving outcomes”.

There are good reasons why the amount of research in this area, and the acquisition of independent data sources by manufacturer sponsors have been limited. The results of such studies, and the use of independent data carry risks of coming to conclusions that can’t be readily commercially used. If a claim that is derived from the study is not in-line with the approved label, then the time, effort, and money spent on the study has effectively been wasted. By providing guidance and allowing for off-label promotion, FDA effectively incentivizes market access and brand teams to fund differentiated and alternative research, as well as seek out independent data sources. Thus providing healthcare decision makers with types of data that they are asking for to make fully informed CER decisions. With more research being conducted as a result of restrictions being lifted on off-label promotion, the transparency push will lead to more data being published, both positive and negative, leading to a less biased data pool.

All of the potential benefits from off-label promotion are contingent on FDA making smart decisions in the coming months that balance the need for a centralized authority on drug safety with the need for increased flow of data and information. It will be interesting to see the results of the open meeting they hold this summer on the topic.

In the meantime, we at AdverseEvents will continue to provide healthcare decision makers the independent, unbiased comparative safety research they demand. Click here for a Cost Comparison and Safety Analysis of Eylea vs. Lucentis for Diabetic Retinopathy.


Written by Jim Davis

EVP, AdverseEvents

As Executive Vice President, Jim manages the company’s global sales and business development efforts. Jim brings over 12 years of experience in commercial strategy, global sales management and execution, business development, and product development. He has over 9 years of specific domain expertise in biopharma market research, intelligence, and data.

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Adding value to biomedical endpoints – The Importance of Patient Reported Outcomes (PROs)

The challenges

A key hurdle facing the entire pharmaceutical industry is non-adherence by patients to medication. This problem is only likely to be surmounted if patients believe that taking medication will lead to immediate benefits through reduction of symptoms, improvement in physiological functioning and quality of life.

The  diabetes mellitus (DM) marketplace, for example, is becoming saturated with multiple medications in both the insulin and pre-insulin space, particularly as analogues start to lose their patents. Differentiation in clinical outcomes within classes is often unclear or minimal. This means that differentiation of therapeutic options is likely to focus more on frequency or mode and method of administration, as opposed to statistically significant differences in glucose control, which are clinically relevant.

What is a measurement strategy?

An effective way of establishing the link between the measured outcome, such as the patient’s health status or quality of life following an intervention programme, is the development of a measurement strategy which requires a clear understanding of the disease and the relevant primary outcomes (e.g. reduced hypoglycemia and secondary outcomes e.g. reduced anxiety).

A patient-reported outcomes (PRO) measurement strategy provides a framework to support the selection of an appropriate PRO for a clinical trial through which treatment effectiveness in terms of health status or quality of life for example, can be demonstrated in relation to the desired primary outcomes.

Components of each of the key stages of the strategy are shown below.  This strategy makes explicit the expected treatment effects (e.g. primary biomedical endpoint(s)) AND IMPORTANTLY  the secondary endpoints such as reduced anxiety, to be measured by the PRO.

pro measurement strategy

A critical aspect of the measurement strategy is selecting the appropriate PRO that captures  the benefits of the primary physiological endpoint of treatment i.e. secondary endpoint(s). However, outcome teams are frequently faced with a plethora of potential PROs each purporting to measure – often without a sound theoretical or measurement model – specific health constructs such as health status or quality of life.  As a consequence the choice of a PRO is often made according to:

  •  the instrument having been used in previous studies
  • its name appears to be appropriate for the intended use
  • The supporting psychometric data looks o.k.

Furthermore, there is the tendency for those conducting clinical trials to treat the more commonly measured health constructs such as quality of life (QoL), health-related quality of life (HRQoL) and health status as interchangeable in the PRO selection process which they are not. Examples of this include the SF-36 and EQ-5D which are frequently referred to as indicators of QoL, but in fact are more indicators of health status, which of course can impact on the individual’s QoL. Health status is a measure of the quality of health yet while there is no universally accepted definition of QoL, there is the general consensus that it is based on the individual’s subjective evaluation of the psychological and social aspects of their life including work, school and family.

As described above, essential to selecting the appropriate PRO is to make explicit the expected treatment effects e.g. primary biomedical endpoint(s) and the resulting secondary endpoint(s) which should be articulated through the endpoint model  from which the most appropriate PRO can be selected. For an example of a simple endpoint model see below.

Microsoft Word - Docendpoint model.docx

In this simple model, the objective is to reduce recurrent hypoglycemia which – as the primary endpoint – will be a reduction in the various effects of hypoglycemia including sweating, shaking. etc.  Then, as a result, an improvement in the the desired secondary endpoint of the patient’s quality of life will occur.  Clearly the model requires further expansion to include which elements of QoL are to be measured as well as health status.  Having specified the secondary endpoints the appropriate PRO can then be selected. Central however, to selecting the PRO is the PROs conceptual framework.

What is a PRO conceptual framework?

The PROs conceptual framework  shows the item content in relation to the specified concepts/domains the instrument is purported to measure. Therefore, if the PRO has been selected to measure aspects of sleep disturbance as a secondary endpoint, then there must be clear conceptual and psychometric evidence that the items of the PRO should relate directly to these specific construct. Below as an example is the conceptual framework of the Diabetes Health Profile -a PRO developed to assess the psychological and behavioural impact of living with diabetes that was derived on the basis of significant patient input and psychometric evidence.

DHP-1-Conceptual-framework copy

Not all PROs make explicit their conceptual framework, but it’s worth bearing in mind that evidence 0f a conceptual framework  is an essential requirement by the FDA for labeling claims


Selecting the most appropriate PRO to provide evidence of treatment effectiveness based on the patient’s perspective is a complex process requiring an explicit measurement strategy. This will include defining the primary endpoints and their relationship(s) with the desired secondary endpoints and linking these with conceptual framework of the selected PRO.

keith2 croppedDr Keith Meadows is Founder and Director of DHP Research and Consultancy Ltd. Keith has extensive experience in the field of patient reported outcome measurement with a particular emphasis on the psychological impact of living with diabetes.

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