Drug Saf https://doi.org/10.1007/s40264-017-0632-0

COMMENTARY

The Safety of Generic Prescription Drugs in the United States Sonal Singh1

Ó Springer International Publishing AG, part of Springer Nature 2018

1 Introduction ‘Then you should say what you mean,’ the March Hare went on. ‘I do,’ Alice hastily replied; ‘at least—at least I mean what I say—that’s the same thing, you know.’ ‘Not the same thing a bit!’ said the Hatter. ‘You might just as well say that ‘‘I see what I eat’’ is the same thing as ‘‘I eat what I see’’!’ ‘You might just as well say,’ added the March Hare, ‘that ‘‘I like what I get’’ is the same thing as ‘‘I get what I like’’!’ ‘You might just as well say,’ added the Dormouse, who seemed to be talking in his sleep, ‘that ‘‘I breathe when I sleep’’ is the same thing as ‘‘I sleep when I breathe’’!’ Alice in Wonderland, Chapter VII—‘‘The Mad Tea Party’’; Lewis Carroll 1865 [1] These lines capture the dilemma faced by patients, physicians and policy makers who grapple with the challenge of deciding whether their generic prescription drugs are like their brand name counterparts. Approximately nine out of every ten prescriptions filled in the USA constitutes & Sonal Singh [email protected] 1

Department of Family Medicine and Community Health and Meyers Primary Care Institute, University of Massachusetts Medical School, 55 Lake Ave North, Worcester, MA 01655-0002, USA

a generic drug [2]. There have been recent efforts to speed up generic approval in the USA with 2017 seeing the highest number of abbreviated New Drug Applications (NDAs) for generic drugs. However, despite the widespread use of these drugs, physicians and patients have expressed concerns about the side effects of generics relative to brand name drugs [3]. Several recent examples of the therapeutic failure of marketed generics have added to these concerns. In 2014, the US Food and Drug Administration (FDA) declared that two of three available generics for Concerta in the USA were neither bioequivalent nor interchangeable with their reference product [4]. These findings were later confirmed in a disproportionality analyses of reports from Canada [5]. The concerns about safety of generics are not limited to patients, but extend to other stakeholders including physicians and pharmacists [3]. While there has been a rise in the acceptance of generic drugs, with some stakeholders favouring importation of generics from Canada, the lack of quality control at several product manufacturing sites of prominent manufacturers outside the USA has accentuated concerns about their safety [6].

2 Challenges in Studying Generic Drug Safety There are several challenges in studying the safety of generic drugs relative to brands. The data base of safety for generic drugs is small compared to their brand name counterparts because their approval relies on demonstration of equivalence as measured by maximum concentration (Cmax), area under the curve (AUC) and partial area under the curve (pAUC) [7, 8], as compared to the demonstration of efficacy and safety in adequately powered randomized

S. Singh

controlled trials required for brand name prescription drugs. The safety of generics relies on the presumption of the safety of the brand product at the time of approval, which might not be comprehensive because safety of prescription drugs is continuously assessed and updated, as evident by withdrawals and boxed warnings after their approval [9]. The FDA’s Adverse Event Reporting System (FAERS) is an important source of information that has informed the withdrawals of and/or warnings on prescription drugs in the USA. However, this passive surveillance system has several limitations, including the reliance on voluntary reporting, lack of clinical details, duplication of data and lack of a denominator. A recent study that evaluated the completeness of reports submitted to the FDA, reviewing age, gender, event date and one outcome of interest, noted that completeness of reporting varied from 25.4% complete on all variables to 67% complete when evaluating the performance of manufacturers submitting more than 5000 reports [10].

3 Recent Studies to Identify Generic Drugs in the FDA’s Adverse Event Reporting System The first step in studying generic drug safety relies on accurate identification of the relevant drugs in FAERS. In a recent study in an earlier issue of Drug Safety, we developed a three-item algorithm including the criteria manufacturer name, NDA number/abbreviated NDA (ANDA), and specific use of the term ‘generic’ or ‘brand’ to classify three drugs (tamsulosin, levothyroxine, and amphetamine/ dextroamphetamine) of each case report as generics or brands. We obtained data from the publicly available FAERS and source case narratives obtained from the FDA under the Freedom of Information Act (reference standard) [11]. We classified 15.8, 9, and 16.7% of reports of tamsulosin, levothyroxine and amphetamine/dextroamphetamine as generics with high inter-rater reliability. We were unable to classify more than one-third of reports due to incomplete information. Among those drugs that were not classified as generics in the publicly available data, more than one-fifth were reclassified as generics using the source narratives. Another review of 2500 reports found that the suspected product type could not be accurately identified as brand or generic in 84% of reports of five antiepileptic drugs [12]. Most reports were sent by brand name manufacturers despite the high rates of utilization of generics. Another study, by the Institute of Safe Medication Practices, evaluated generic drug reporting in their publication QuarterWatch using the example of sertraline and found that in 2013 brand name sertraline accounted for 0.7% of dispensed outpatient prescriptions, but 65% of the

serious adverse event reports [13]. These studies highlight the limitations of using FAERS data alone to study the safety of generic drugs.

4 Comparing the Safety of Generic with Brand Name Drugs In this issue of Drug Safety, the authors provide additional insight into the safety of generic drugs [14]. The authors compared differences in suicide and suicidal ideation reporting rates for four brand versus generic central nervous system (CNS) drugs (sertraline, gabapentin, zolpidem and methylphenidate) using complementary study designs. They conducted a hypothesis-generating disproportionality analysis using the publicly available FAERS database, where they found lower suicide reporting rates for all four brands compared to generics (Breslow–Day P\0.05). They also conducted a hypothesis-testing study using a retrospective cohort design. This included an insured population in the Security Health Plan and used electronic health records obtained from the Marshfield Clinic. After adjusting for various confounders including smoking and Charlson Comorbidity Index score, only generic sertraline showed a statistically significant reduction in the rates of suicide [hazard ratio (HR) 0.58; 95% confidence interval (CI) 0.38–0.88] which was in the order of 42%, although the CIs were somewhat imprecise. Their study has several strengths. They included a mixed methods approach which included both a hypothesis-generating and hypothesis-testing component in two complementary databases. They adjusted for various known confounders including smoking, diabetes and the Charlson Comorbidity Index and background suicide rates in their analysis. They used Standardised Medical Dictionary of Regulatory Activities (MedDRA)Ò Queries to identify suicide in the FAERS database, where identification of suicide is challenging [15]. Although they used algorithms to identify suicide in their retrospective analysis, the ability of any algorithm to diagnose suicide is challenged by the complexity of suicidal behaviour and separating intentional from unintentional self-harm. The definitions of suicide across the two studies were reconciled through expert consensus by mapping the Standardised MedDRA Queries and Preferred Terms in FAERS to International Classification of Disease-9 (ICD-9) codes in the cohort study. However, the study has several limitations which preclude us from drawing definitive conclusions. Studying suicide in FAERS is particularly challenging given the heterogeneity of definitions for suicide, including suicidal ideation, suicidal intent, completed suicide and intentional self-harm. This was further compounded by the lack of

The Safety of Generic Prescription Drugs in the United States

access to source narratives. The challenges in the proper identification of generic or brand name drugs in FAERS outlined above may have biased the findings. The cohort study was limited by the lack of a prospective assessment of suicide, which may limit ascertainment. The temporal influence of boxed warnings for suicidality coincided with the introduction of generic sertraline, which limited the investigators’ ability to adjust for collinear effects. They were unable to determine whether the effects of generics versus brands varied by dose and cumulative exposure. The prescriptions dispensed may not reflect prescriptions taken in any database study. While the investigators adjusted for a range of confounders, confounding by unknown confounders is always possible. The generalizability of these findings beyond the study population is also unknown.

prescription drug safety [24] because patients trust their physicians as a reliable source of information. The elusive and evolving concept of prescription drug safety is best exemplified by the epistemological framework of ‘‘dependant arising’’ set forth by the ancient Ayurvedic physician Nagarjuna, which states that ‘‘If this exists, that exists, if this does not exist, that does not exist’’ [25]. Drug safety is neither absolute nor permanent and can only be understood in the context of efficacy. The only truly safe drug is the one that we have never taken. Compliance with Ethical Standards Funding No sources of funding were used to assist in the preparation of this commentary. Conflicts of interest Sonal Singh has no conflicts of interest relevant to the content of this commentary.

5 Looking Ahead Despite these limitations, there are several important conclusions that can be drawn from recent studies of prescription drug safety of generics and brand name drugs. First, continued post-marketing surveillance with an eye towards uncovering differences between generics and brand name drugs is needed. The availability of the recently available FAERS Public Dashboard has increased our potential to conduct additional drug safety studies using several different classes of prescription drugs on a range of outcomes [16]. However, its full potential can only be realized with accurate identification of the brand or generic drug. The prescription drug bottles or packaging should contain the manufacturer’s name and classification as a generic or brand name drug. Placing hard stops in the FAERS will also improve the completeness of reporting. Linking adverse events noted in electronic medical records directly to FAERS should also be explored. We should also collect data on patient-oriented outcomes in adverse event reports [17]. Methodological studies within the Sentinel distributed research network and other claims-based databases are needed to develop reliable and valid algorithms that classify drugs accurately as generics or brands and ascertain any relative differences in safety. Observational studies and robust meta-analysis of adverse effects will continue to serve as an important source of information on adverse effects of prescription drugs [18]. Replicating both systematic reviews and meta-analysis of adverse effects [19, 20] and observational studies [21–23] using complementary study designs and databases will increase our confidence in their findings. Shared decision-making approaches can easily be adopted to improve patient– physician communication and understanding around

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18. Zorzela L, Loke YK, Ioannidis JP, Golder S, Santaguida P, Altman DG, et al. PRISMA harms checklist: improving harms reporting in systematic reviews. BMJ. 2016;352:i157. 19. Onasaya OIG, Lucas E, Lin D, Singh S, Alexander GC. Association between exogenous testosterone and cardiovascular events: an overview of systematic reviews. Lancet Diab Endocrinol. 2016;4(11):943–56. 20. Alexander GCIG, Lucas E, Lin D, Singh S. Cardiovascular risks of exogenous testosterone use among men: a systematic review and meta-analysis. Am J Med. 2017;130(3):293–305. 21. Abraham NS, Singh S, Alexander GC, Heien H, Haas LR, Crown W, et al. Comparative risk of gastrointestinal bleeding with dabigatran, rivaroxaban, and warfarin: population based cohort study. BMJ. 2015;350:h1857. 22. Chang H-Y, Zhou M, Tang W, Alexander GC, Singh S. Risk of gastrointestinal bleeding associated with oral anticoagulants: population based retrospective cohort study. BMJ. 2015;350:h1585. 23. Tang W, Chang H-Y, Zhou M, Singh S. Risk of major gastrointestinal bleeding among dabigatran users: a populationbased, new-user, self-controlled study. J Patient-Cent Re Rev. 2017;4(3):181. 24. Maruthur NM, Joy SM, Dolan JG, Shihab HM, Singh S. Use of the analytic hierarchy process for medication decision-making in type 2 diabetes. PLoS One. 2015;10(5):e0126625. 25. Westerhoff J. Na¯ga¯rjuna’s Madhyamaka. A philosophical introduction. Oxford: Oxford University Press; 2009.