Analysis of data more accurately different describing the geographic distribution of Avastin (ie, prescribing and/or reimbursement data) and US cancer incidence/prevalence data has the potential to address this limitation, but was beyond the scope of this study.
Further, there is no data that confirms how many patients were administered or otherwise received treatment with a counterfeit version of Avastin. Hence, our results and any potential conclusions on the impact of counterfeit Avastin are limited based on the data analysed. Despite these limitations, these data, to the best our knowledge, are the most representative available compilation of addresses for potential counterfeit cancer medication exposure in the USA. The demographic variables analysed in this study were those made publically available along with geospatial data packaged for analysis through the use of geospatial software. Though these 44 characteristics provide a preliminary understanding of demographic differences by counterfeit notice receipt status, possibilities for redundancy and incompleteness exist. For example, the variables that
represent the number of individuals within certain age groups may serve as a proxy measure for susceptibility to several cancers that are treatable with Avastin, thereby increasing the possibility that this age group is more highly prescribed Avastin, which in turn increases the possibility that they went to a clinic that purchased and administered a counterfeit version. A similar limitation may apply to the variable of individuals over age 65, as these individuals may have greater access to healthcare services/coverage through their eligibility for enrolment into Medicare, resulting in higher levels of access to Avastin treatment. Given
the high price of Avastin, a measure of health insurance coverage might also be confounded by income, as income may also equate to increased treatment access through additional enrolment into a supplemental Medicare insurance programme. Therefore, while measures of income and insurance coverage were omitted from this Cilengitide study, further exploration of the complex multivariate relationships between Avastin financing, economics and access are needed to further validate study results. Strengths This is the first study, to the best our knowledge, to simultaneously use statistical analysis and geospatial modelling to analyse the distribution of counterfeit cancer medication and their associated demographic risk characteristics. This article further strengthens this recommendation by suggesting that the designation of correlates a priori may be more useful to guide surveillance efforts when compared to intuitive designation of correlates a posteriori.
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