| Literature DB >> 30089508 |
Alex Hodkinson1, Kristina Charlotte Dietz2, Carol Lefebvre3, Su Golder4, Mark Jones5, Peter Doshi6, Carl Heneghan7, Tom Jefferson7, Isabelle Boutron8, Lesley Stewart2.
Abstract
BACKGROUND: Clinical study reports (CSRs) are produced for marketing authorisation applications. They often contain considerably more information about, and data from, clinical trials than corresponding journal publications. Use of data from CSRs might help circumvent reporting bias, but many researchers appear to be unaware of their existence or potential value. Our survey aimed to gain insight into the level of familiarity, understanding and use of CSRs, and to raise awareness of their potential within the systematic review community. We also aimed to explore the potential barriers faced when obtaining and using CSRs in systematic reviews.Entities:
Mesh:
Year: 2018 PMID: 30089508 PMCID: PMC6083614 DOI: 10.1186/s13643-018-0766-x
Source DB: PubMed Journal: Syst Rev ISSN: 2046-4053
Important criteria when considering data from clinical study reports and/or other regulatory data
| Criteria | Description of criteria |
|---|---|
| 1 | Monetary cost of the intervention on the healthcare budget (i.e. considering both the price of a course and the number of people in the population that are being—or will be—treated) |
| 2 | Burden of disease of the indication this product is meant to treat/prevent |
| 3 | How many people are using or likely to use this product? |
| 4 | Product new to the market? |
| 5 | Product from a new drug class or has a new mechanism of action |
| 6 | Has important interactions with other drugs (e.g. drug-drug interactions) |
| 7 | High proportion of RCTs evaluating this product are industry funded |
| 8 | Prominent claims of safety and/or efficacy advantage of this product over currently available treatments |
| 9 | High degree of media attention surrounding this product |
| 10 | High proportion of trials of this product are unpublished |
| 11 | Post-marketing surveillance has identified safety concerns? |
| 12 | Important or standard outcome measures (also known as ‘endpoints’) have not been published |
| 13 | Concerns regarding a lack of published data on potential harms of the product |
| 14 | Marketing authorisation based on surrogate outcomes (rather than clinical outcomes) |
| 15 | When protocol(s) are publicly available |
| 16 | When statistical analysis plan(s) publicly available |
| 17 | Known errors or concerns about trial publications of this product |
| 18 | Important discrepancies between the journal publication and the trial registry entry? |
Fig. 1Flow diagram of combined survey responses with responses in each domain of interest
Fig. 2Sources of data for the respondents who requested regulatory/non-regulatory data and the success rate obtaining the data. *Larger companies include GSK (n = 1 request (1: successful request)), Pfizer (n = 2 (2)), Eli Lilly (n = 1 (1)), Bristol-Myers Squibb (n = 2 (1)), Merck (n = 1 (0)), Genentech (n = 1 (1)). **Smaller companies include (2) Helsinn, (2) Schering-Plough, (1) Salix Pharmaceuticals, (1) PharmaSwiss, (1) Cubist Pharmaceuticals, (1) Pharmaxis, (1) Santhera. **(1) Request was made to the US’s National Institute for Occupational Safety and Health (NIOSH) and the other to Health Canada
Description of data obtained and how they were used in the systematic reviews
| Survey reply | Source of data request(s) | Data obtained | Type of regulatory data/document(s) obtained | Included in meta-analysis | Description of how data were used |
|---|---|---|---|---|---|
| 1 | Author, manufacturer | Yes | CSRs | Yes | ‘Summary statistics provided or extracted from the extra documentation were incorporated into meta-analysis’ |
| 2 | Unknown | Yes | CSRs | Yes | ‘Quantitative data about side effects were included’ |
| 3 | EMA, FDA | Yes | CSRs | No | ‘Data were not used in meta-analyses, but rather in a narrative form instead’ |
| 4 | EMA, FDA | Yes | EPARs and Medical Reviews | No | ‘Data was used to describe the number of studies and the number of studied drugs in results of search criteria’ |
| 5 | EMA, FDA, Multiple drug companies | Yes | FDA and EMA reports, Poster | Yes | ‘To add data on studies not aware of, and to add outcomes to a published study that were not itemised in the journal publication’ |
| 6 | Clinical investigator, EMA, sponsor | Noβ | No data were obtained | N/A | ‘Not provided by pharmaceutical sponsor, possibly because study stopped early due to unexpected side effects, and raw data may never have been compiled.’ |
| 7 | FDA, Health Canada, NIOSH | Yes | Adverse event reports | No | ‘The data did not provide some of the detail we would have liked, such as indication for the drug, dosing etc. We summarized the results in narrative form but did not include in the quantitative analyses of the data we retrieved from published studies’ |
| 8 | Clinical investigator, medical director of company | Yes | CSRs | Yes | ‘Assessed quality of the studies and extracted data for use in forest plots and description’ |
| 9 | Clinical Study Data Request, EMA, FDA | Other* | Case report forms | N/A | ‘N/A as data not received’ |
| 10 | Clinical investigator, EMA, Pharmaceutical company | Other¥ | Details of trial participants at start of trial (baseline data and info about randomisation) | No | ‘Only data at start of trial was available’ |
| 11 | EMA, GSK and FDA | Yes | Clinical and Statistical reviews at FDA, CSRs | Yes | ‘We checked the data for consistency (across multiple published and unpublished sources) and reported in the systematic review the most accurate and conservative estimates. If needed, we contacted authors for confirmation’ |
| 12 | Pharmaceutical company | Yes | CSRs, IPD | Yes | ‘Data from CSRs & IPD were used in evidence synthesis’ |
| 13 | Pfizer | Other* | CSRs | N/A€ | ‘Extraction of data from Pfizer Medical Information Report’ |
| 14 | EMA, FDA | Yes | CSRs, protocol with appendices | Yes | ‘We extracted, compared and used the aggregated effect estimates data for predefined outcomes’ |
| 15 | Helsinn, Merck and Pfizer | Yes | CSRs | Yes | ‘Where possible incorporated it as more likely to be the correct data than what was published’ |
| 16 | EMA, FDA | Yes | FDA medical and statistical reviews | Yes | ‘Performed data extraction from these sources. Compared with data from published sources’ |
| 17 | EMA, NIOSH | Yes | N/A | No | ‘Excluded studies’ |
| 18 | FDA | Yes | CSRs, FDA reports and IPD | Yes | ‘Data was used in place of publication’ |
| 19 | YODA | Yes | CSRs | Yes | ‘Data were used in network meta-analyses’ |
| 20 | Bristol-Myers Squibb, Genentech, Schering-Plough | Yes | CSRs | No | ‘In narrative synthesis. However, some of the data/text needed to be removed before the final technology assessment report is published under the confidentiality agreement’. |
N/A not applicable, FDA Food and Drug Administration, EMA European Medicine Agency, NIOSH The National Institute for Occupational Safety and Health
βResponse: ‘data not provided by pharmaceutical sponsor possibly because study was stopped early due to unexpected side effects and therefore the raw data may not have been complied’
*Still awaiting data/updating review
¥Intended data requested was not available
€Intend to incorporate data in a meta-analysis
Barriers when seeking regulatory data for use in a Cochrane review
| Requested/used regulatory data | Considered regulatory data | Not considered regulatory data | |
|---|---|---|---|
| Survey question | Total no. of responses: n (% of total responses) | ||
| Are there any barriers to using regulatory data? | |||
| Yes | 14 (70) | 6 (86) | 67 (50) |
| No | 2 (10) | 0 (0) | 10 (8) |
| Unsure | 4 (20) | 1 (14) | 56 (42) |
| What were these barriers? | |||
| Restricted and limited sharing of data | 8 | 4 | 31 |
| Time-constraints | 6 | 2 | 17 |
| Lack of experience (inc. statistical) | 4 | 1 | 21 |
| Identifying/searching for trials | 2 | 1 | 13 |
| Quality of data | 1 | 0 | 12 |
| Cost | 0 | 1 | 1 |
| Effort/resources required | 0 | 0 | 5 |
| Limited access for peer reviewers* | 0 | 0 | 1 |
*This referred to peer reviewers not having access to regulatory data during the peer review stage
Fig. 3Criteria considered most important when considering using regulatory data (n = 14)