This is as if disclosing the financial sources behind a study is not necessarily a requirement by publishing journals. This is particularly true in the s and s, before many of the reporting guidelines were published, 18—25 which may especially explain the lower disclosure rate reported by Buchkowsky and Jewesson in the same period. The industry funding was significantly increasing, resulting in about similar overall prevalence to the non-profit organisations funding by This is not consistent with the literature studies, by Lexchin et al 26 and Buchkowsky and Jewesson, 17 whereby the prevalence of industry funding was reported to be lesser than other types of research funding.
It is important to note here, however, that the Lexchin et al and Buchkowsky and Jewesson studies were simply focusing on the clinical trials research and up to the year only.
The Cost of Cancer Treatment Study (CCTS) was designed to address . data for from the Centers for Medicare and Medicaid Services as an Costs were predicted using consistent retransformation methods that. the year stage of disease not enrolled in a research protocol from 83 cancer clinical research . which is an efficient method for iden- †For inclusion in the Cost of Cancer Treatment Study, living participants must have completed a .
The latter is actually in support of our study, where the size of the industry funding was overtaken by the other funding sources until early s. Also, clinicians are perhaps less inclined to generally conduct CEA research when compared with clinical research, without the availability of industry funding. The observation of an increasing trend of industry funding over time was consistent with the literature reports, by Clifford et al 27 and Buchkowsky and Jewesson, 17 in relation to clinical trials in five selected medical journals in the literature.
The pharmaceutical industry authorship was at an increasing trend over time. There is an increase in consultation authorship over time and at a higher rate than the industry authorship. It is assumed, therefore, that the contraction of consultation firms by the pharmaceutical industry in relation to the cancer CEA is also increasing. The surprising thing in relation to the publications with paid consultation involvement is that in over quarter of them, the source of the study funding was not disclosed.
Changes in the quality status of economic evaluations overtime do not seem to be a factor behind changes in the above study's variables overtime. Included studies were in average of good quality. While the evaluations in the first study block were generally less than good, they were not poor, and few in number.
The majority of studies reported positive outcomes in favour of the study drug ie, Here, disseminating negative research findings is an issue that gains traction, whereby journals are increasingly publishing negative results, including via specialised journals. The economic outcome of a study intervention tended to more statistically significantly be positive in studies that are solely industry funded than in studies with non-declared or non-profit funding. It is important that, as discussed above, differences in study quality can be excluded as a confounding factor behind differences in the rate of positive outcomes among the different sources of study funding.
The potential association between industry funding and reported study outcomes was extensively investigated in the literature. Large literature reviews were reported by Lundh et al 34 and Lexchin, 35 suggesting an evidence that industry-funded studies produce biased results. These however only analysed clinical trials, with pharmacoeconomics being out of scope. A wider scope review of systematic reviews was reported by Schott et al , 36 where 26 publications were reported to have had investigated the possible relationship between the industry funding and favourable study results for interventions.
In agreement with our study, 20 of these suggested that a statistically significant association existed. Nevertheless, these reports were of clinical trials only.
There are other studies that especially evaluated the funding influence within the pharmacoeconomics research. Friedberg et al 7 reported a reduced likelihood of unfavourable results in industry-funded studies, but this was in and only included three drug classes. The study by Hartmann et al 8 also reported a significant association, but this was in , only related to oncology. Jang et al 9 reported the significant influence as well, but this only related to breast cancer therapies. Similar conclusion was also more recently reported by Valachis et al , 10 but only related to targeted therapies in oncology and only included clinical trials.
To emphasise, the conclusion made in the current study relates to the isolated industry funding only, in separation from the mixed type of funding. This better suggests the isolated influence by the pharmaceutical companies. This separation was not taken in consideration by the relevant literature, except for the study by Buchkowsky and Jewesson.
This is consistent with the current study, in relation to the mixed funding. There are several potential reasons behind this connection between industry funding and positive study results. There is evidence that pharmaceutical companies often influence the study methodology to their advantage. There are already several published research reporting guidelines for reporting the different aspects discussed in this study, 18—25 including in relation to the pharmacoeconomics research, that is, CHEERS.
There are several strengths in the current study. The reviewed studies are not from selected journals, which enhance the external validity of results. In addition, the year duration of follow-up in this study is sufficient and larger than in similar literature studies.
Further, this is the first study to explore the CEA literature of cancer therapies, and in relation to the association between industry funding and study results, this is the most comprehensive. Moreover, an assessment of the quality studies was conducted for the exclusion of this as a confounding factor.
There are several limitations with our study.
While it is acknowledged that studies of different types of cancer or chemotherapies have different levels of priority for decision makers, the scope of the present study is in relation to the comparative literature studies in general, with no special interest given to any particular type of cancer or therapy.
Restricting search to English literature is another limitation in the study. The authors do not have the resources to translate all the non-English research literature that generated from a non-restricted search, which include, for example Chinese, French, German, Japanese and Russian. This is when including certain non-English language literature while excluding others is not justified. Nevertheless, this is not a therapeutics review where looking at every relevant publication is required and, in any case, this study's observations are limited to the scope of the restricted search, For our purpose, the English-based literature is considered representative of scientific literature.
Moreover, while comprehensive literature search was indeed conducted in this study, relevant studies could have been also explored in other literature databases that may include Global Health, Health Economic Evaluation Database, Cost-effectiveness Analysis Registry, Open Grey and Information technology Assessment international. This study does not review the literature at the therapy level, where no conclusions are made in relation to use of therapies in practices and the evidence. Ongoing research, however, does exist in relation to assessing CE of chemotherapies and making recommendations for best evidence-based use in clinical practices.
Also a limitation is that while different journals have varying publication criteria, all journals were weighted equally in this study, which can be associated with bias. This publication bias is anticipated to be minimised, however, due to how thorough the search strategy was, which included s of articles of all types, from all settings, from all perspectives, from all journals, in relation to all therapies for all cancers, and over a very long duration.
In addition, our selection of 5 time periods was arbitrary, and other methods could yield different results. Nevertheless, the number of time points we used is more than that used in similar published research. Literature journals are gradually more interested in publishing CEA investigations, particularly in journals that clearly focus on the health economic research. Our findings also indicate that researchers are increasingly relying on less than ideal source of data ie, retrospective data , when compared with the prospective. The industry funding of research is prevalent and increasing over time.
The industry authorship is also increasing in publications, but to a lesser extent than that by paid consultation firms. In this study, we suggest that the evidence that a CE evaluation of cancer therapies may not report a result that is not positive is stronger with sole pharmaceutical industry funding than with other funding sources. The findings in the current study enable several opportunities for the researchers, journal editors and reviewers, and the decision makers to enhance the CE literature in cancer as they conduct, revise and appraise research and synthesise evidence.
DA-B conceived and designed the study, participated in data collection and analyses, interpreted results and drafted the manuscript. MA and RA-O performed data collection and revised the manuscript. All authors read and approved the final manuscript. Provenance and peer review: Not commissioned; externally peer reviewed. No additional data are available. National Center for Biotechnology Information , U. Published online Jan Correspondence to Dr Daoud Al-Badriyeh; aq. For permission to use where not already granted under a licence please go to http: Abstract Objective To perform a first-time analysis of the cost-effectiveness CE literature on chemotherapies, of all types, in cancer, in terms of trends and change over time, including the influence of industry funding.
Setting A wide range of cancer-related research settings within healthcare, including health systems, hospitals and medical centres. Participants All literature comparative CE research of drug-based cancer therapies in the period to Primary and secondary outcome measures Primary outcomes are the literature trends in relation to journal subject category, authorship, research design, data sources, funds and consultation involvement.
Results Total publications were analysed. Conclusions This analysis demonstrates clear trends in how the CE cancer research is presented to the practicing community, including in relation to journals, study designs, authorship and consultation, together with increased financial sponsorship by pharmaceutical industries, which may be more influencing study outcomes than other funding sources. Cost-effectiveness, Cancer, Therapy, Trends. Strengths and limitations of this study. This is the first literature audit of the cost-effectiveness research in cancer therapy, which reported important characteristics in relation to journals, study designs, authorship, consultation and funds.
The study is the first comprehensive analysis of the association between industry funding and results of economic studies on chemotherapies use, of all types, in cancer. Although all journals were weighted equally in relation to the quality of their publications, it is anticipated that potential bias and confounding is minimised due to the thorough and diverse types of included studies. Inclusion and exclusion criteria The inclusion criteria are: Publication between 1 January and 31 December Definitions The drug therapy was defined as any chemical used as curative, adjunct, palliative or maintenance chemotherapy in a cancer-related disease.
Study publications were mainly classified according to: The medicine category in this classification is used to include several categories relating to any journal that is of a subject category concerning the subject of medicine, including those relevant to specific body systems as subject categories. There is no journal discipline of pharmacoeconomics that officially exists. Nevertheless, for the purpose of this study, a comparative pharmacoeconomics category of journals was created, which included journals from across all subject categories that have announced especial interest in publishing pharmacoeconomics research as part of their scope.
The journal that is classified under more than one subject category was considered under the subject category where it was ranked the highest based on impact factor relative to the other journals in the category. Method of research; retrospective non-RCT or meta-analysis that does not rely on published RCT data and is based on other historical resources, for example, medical records, prospective non-RCT or meta-analysis that does not rely on RCT data and is based on other prospective resources, for example, prospective medical record data, RCTs retrospective that relies mostly on extracted data from already published RCTs, RCTs prospective that relies mostly on prospectively extracted data from ongoing RCTs, meta-analysis retrospective or prospective.
Source of funding; not declared, non-profit, pharmaceutical industry, combination of non-profit and pharmaceutical industry. For studies with non-declared sponsor, an industry funding source was assumed if the study drug supplies were provided by, and one or more authors were affiliated with, that particular pharmaceutical sponsor. The status of authorship was achieved if one or more study authors were affiliated with the organisation. This does not include potential conflict of interest due to relationship with an organisation, that is, personal funding, consultation role.
Declaration of details of potential conflict of interest; there is a conflict, there is no conflict and not indicated. Reported study outcome; outcome is in favour of the study drug over control positive outcome , study drug is equivalent to control, outcome is in favour of control over study drug negative outcome. The size of the outcome difference was not taken in consideration. This is due to the relative nature of the economic outcomes and their importance , and the lack of a standardised tool to assess this. Data collection and statistical analysis Authors completed data collection, populating a variable database.
Open in a separate window. Quality assessment To further understand the changes in study variables overtime, the quality of economic studies was assessed over the study time blocks as a potential confounding factor. Results The literature search generated publications that met the inclusion criteria in the current study figure 1. Research methodology employed The vast majority of CEA studies were retrospective in nature; involving studies that are retrospective but non-RCT or meta-analysis , and studies that are based on retrospective RCT data.
Study funding Over the study period, the source of funding was as follows: Drug supply by company The study drug was supplied by the drug manufacturer in only 61 of studies.
Authorship Coauthorship that is affiliated with pharmaceutical companies and consultation firms has increased in number over time, to a total of 89 and 61, respectively. Study outcomes and association with the funding source A positive outcome in favour of the study drug was reported in studies, 80 studies reported an outcome that is in favour of the comparator intervention, and 74 studies indicated equivalent study interventions.
Quality assessment Results of the quality assessment as per the time blocks and sources of study funding can be seen in table 3. Discussion This is the first report to characterise the literature on CE in relation to cancer therapies. Conclusion Literature journals are gradually more interested in publishing CEA investigations, particularly in journals that clearly focus on the health economic research. World Health Organization American Cancer Society, Trends in the lifetime risk of developing cancer in Great Britain: Br J Cancer ; Siddiqui M, Rajkumar SV.
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Ann Pharmacother ; Preferred Reporting Items for Systematic reviews and Meta-analyses: Enhancing transparency in reporting the synthesis of qualitative research: J Med Case Rep ; 7: Basic statistical reporting for articles published in biomedical journals: A total of records were abstracted for an average of 3. We also obtained 1 medical record for each of deceased patients. Medicare data were received for living patients and 82 deceased patients. Table 2 compares the sample characteristics. Our analysis allows for different treatment costs in phase 3 trials, and our overall estimates were adjusted to reflect the national data.
The populations otherwise look very similar, and there were no significant differences in comorbidities. Trial participants rarely changed practitioners to enroll in a trial and did not differ from nonparticipants in their attitudes toward medical care. Nonparticipants more often have breast cancer, are less likely to be nonwhite, are more likely to have Medicare coverage, and are older.
They also were diagnosed more recently. Because our statistical approach does not rely on exact matching, such differences will not induce bias because we include these characteristics in the multivariate analysis. Table 3 shows unadjusted cost differences using alternative samples and sources and measured in dollars. Our primary measure of costs combines information from the medical records, Medicare claims, and occasionally self-reported utilization as described above. As a check on these results, we compared costs from the Medicare claims files for the smaller sample for whom such data were available.
Table 4 shows our main results using the entire sample and adjusting for possible confounding factors. Full regression results are given in Table 4 A of the technical appendix. Overall, trial participation results in a cost increase of 6. Although the CCTS was not powered to consider subgroup analyses, some interesting findings do emerge when the data are analyzed this way. Phase 3 studies had lower cost differences 3. There was not a large difference in incremental costs between academic health centers AHCs and other care settings. The largest difference was by vital status.
Patients who died during trials incurred much higher costs Table 5 suggests why trial participants were more expensive to treat. Trial participants received more physician visits, more expensive tests magnetic resonance imaging, computed tomography, and multiple gated acquisition scans, endoscopies, and nuclear medicine procedures , and more pathology reports. Much of the increased service use was for deceased participants, who used significantly more physician visits, expensive diagnostics, and pathology reports than did deceased nonparticipants. Overall, nonparticipants had more hospital days, but the difference was not significant.
Uncertainty about the incremental costs from trial enrollment has led to uneven policies by insurance companies. Medicare may be the most salient example. It covers "routine costs" associated with clinical trials. The Institute of Medicine recently recommended that Medicare should pay for more than routine costs, at least for selected trials. The definition of routine costs can be unclear, and this language encourages clinical researchers to design research protocols in such a way that the treatment costs will not exceed standard care by too much.
This may explain why the additional treatment costs from trial participation are so small, but it also may have adverse consequences for the clinical investigation. We undertook the CCTS to provide precise and generalizable estimates of the incremental treatment costs associated with nonpediatric clinical trials for cancer treatment. We focused on direct costs for patient treatment since these are the costs that insurance companies might reasonably be asked to pay in the absence of a trial.
Of course, government-sponsored clinical trials involve other administrative and research costs beyond direct care, including staff training, trial administration, analysis, and reporting. These costs, primarily underwritten by the study sponsors, clearly warrant further investigation.
Furthermore, there is evidence that industry-sponsored trials cover more of the costs of treatment, and in fact generate additional income for participating institutions. Our findings suggest that treatment costs for an adult patient enrolled in an NCI-sponsored trial are, on average, 6. Much of the additional cost comes from higher use of physician visits and expensive diagnostic testing.
Fireman et al 12 also found evidence that trial participants had higher rates of ancillary services. We expected that the CCTS would yield larger differences in costs relative to others because our study included health care settings outside AHCs. In fact, we found little difference in incremental treatment costs between AHC and non-AHC providers, which explains why our results are close to what others have found in single-institution studies. In part, this may reflect the success of the NCI's Community Clinical Oncology Program, designed to make trials available in settings where patients already receive their care.
Little published evidence about the nature and scope of such switching exists. Studies of patient characteristics associated with being offered enrollment in a cancer trial 28 , 29 have generally been conducted among patients at academic medical centers and have not examined whether patients had been referred to these institutions from other providers. We find that the incremental cost is associated with more services, especially physician visits, expensive tests, and pathology reports. In a phase 3 study, these services may accrue differentially for patients in the treatment and control arms.
Thus, it is an open question whether patients in the control arm of a trial actually receive more treatment than the nonparticipants in the same institution. This also raises the question of whether trial participants are getting any health benefits for these incremental services. In their review of the literature, Braunholtz et al, 33 found limited evidence for such a "trial effect.
The type of trial also matters. Patients enrolled in early phase studies have much higher additional treatment costs compared with those in phase 3. In part this is due to more aggressive treatment of trial participants in phase 1 or 2 studies relative to phase 3, but also the higher likelihood that these patients will die during the study period. This finding appears in other studies; Wagner et al 11 note that trial participants incurred "substantially higher cost" in the last 3 months of life in their 5-year study at Mayo Clinic, Rochester, Minn.
Patients in trials may prefer more aggressive treatment despite incurable disease. However, we observed no differences between trial participants and nonparticipants in preferences for aggressive care, as measured in our survey. Alternatively, physicians conducting trials may be more aggressive in trying to save trial participants. The higher costs for deceased trial participants also could be an artifact of our inability to identify all the clinicians who served each patient.
Survey respondents saw approximately 4 different practitioners between interview and diagnosis, but we only obtained 1 record per deceased patient. Undercounting utilization will only bias our results if it is systematically different between deceased trial participants and nonparticipants. Based on our telephone survey, trial participants identified seeing only slightly fewer practitioners than nonparticipants 4.
These key elements of phase II design were grouped into seven categories, as displayed in Figure 4. Specifically, although response probably remains the most widely used outcome measure, non-binary definitions or volumetric measures of response, measures of time to event or continuous markers such as biomarkers may be more relevant when evaluating the activity of targeted or cytostatic agents Karrison et al , ; Booth et al , ; Adjei et al , ; Dhani et al , ; McShane et al , The cost weights derived from these regression models were then applied to utilization from the CCTS medical records. Practical considerations Finally, in developing a structured approach to selecting a phase II trial design, it became apparent that practical considerations such as the number of patients available and the need for specialist computer programming would aid selection between alternative designs. MA and RA-O performed data collection and revised the manuscript. Industry sponsorship and research outcome.
Thus, there is little evidence for a systematic bias among the living respondents. There is little evidence that our trial participants differ in unobserved ways from our nonparticipants. Also, some of our nonparticipants were drawn from institutions that did not participate in study trials, so our sample does not include only patients who chose not to participate in a clinical trial. Differential nonresponse by trial participants and nonparticipants was accounted for in our weighting scheme using data provided by institutions on nonrespondents.
Changes in the mix of patients enrolling in trials, or the type of trials being conducted, would likely yield a different result. At the time this study was conducted, Medicare did not routinely pay for medical care incidental to clinical trials. This is no longer the case, and Medicare is also considering what level of inducements would be allowable to encourage trial participation by Medicare beneficiaries.
The question then arises whether the incremental treatment costs vary when the mix of enrollees changes substantially. Estimates from auxiliary models not shown did not find any significant interactions between payer status Medicare and additional treatment costs, but it is not clear whether this is due to a different mix of trials for this population or due to different treatment of Medicare beneficiaries within trials. This is an issue worthy of future research. Of equal import, it may be that an open reimbursement policy could result in greater incremental costs by inducing a behavioral response in the trials that are undertaken, especially in more aggressive trials.
This cost increase presumes that uncertainties about reimbursement in the status quo limit which trials are initiated. Putting aside that eliminating this barrier is likely to accelerate improvements in cancer treatment, it also will result in higher incremental costs than we report herein. Barriers to clinical trials, I: Barriers to clinical trials, II: Barriers to clinical trials, III: Various Factors Affect Patient Participation.
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