This retrospective DUS examined the use of fluoroquinolones through prescriptions in primary care in six countries between 2016 and 2021, and explored whether the EMA regulatory interventions implemented throughout 2018–2019 had any impact on fluoroquinolone prescribing rates. Although we found reductions in prescription rates during follow-up, these were not temporally related to the implementation of regulatory interventions and were inconsistent across countries. Other indicators of changes in prescribing behaviour, such as early discontinuation or prescriptions of alternative antibiotics, were unaffected by regulatory interventions. Our findings did not support a relevant effect of regulatory interventions on fluoroquinolone prescriptions in primary care in the studied countries.

The lack of evident changes after interventions could indicate that these had, at best, low effectiveness and were not detectable in the primary care setting in these countries. Our findings were similar to studies performed in the United States (US). One US study reported a significant decrease in outpatient fluoroquinolone prescribing (by 39% reduction in total prescriptions per 1000 patient visits) after a multimodal stewardship intervention between 2016 and 2018 [12]. Yet, fluoroquinolone use declined before and after a US FDA black-box warning on fluoroquinolones in 2016, suggesting limited impact of regulatory changes [13]. Another US study in a large outpatient centre did not find a significant impact after the FDA black-box warning on fluoroquinolone prescribing trends between 2013 and 2018 [14]. Our findings may also indicate that the timeframe studied was too short to allow adequate dissemination of regulatory measures to healthcare practices and subsequent prescription rates. A systematic review on the effectiveness of UK regulatory risk communications assumed a 12-month lag time to evaluate the effects of country-wide interventions [15]. Although no lag time was implemented in our study, even considering that a 6-month follow-up time at study end was excluded, we would still have been able to observe any changes in fluoroquinolone prescriptions.

Possibly, one may argue that observing a lack of changes associated with regulatory interventions suggests that the data were somehow not well reflective of clinical practice. Yet, study setting and design support that the data reflect GP. Moreover, the absolute levels of fluoroquinolone prescriptions, the prescription patterns across countries, age groups, and main indications, and the avoidance in risk groups aligned well with known country differences and clinical guidelines [16,17,18].

Detection of any effect of regulatory interventions may have been obscured by decreases in prescriptions rates already occurring before implementation of regulatory interventions. In the UK, although the decreases started before implementation, regression analyses showed a reduction in prescriptions that later coincided with SmPC changes and DHPCs. Timing of this reduction also corresponded to EMA communications regarding fluoroquinolone restrictions (16 October 2018, Pharmacovigilance Risk Assessment Committee [PRAC] recommendation; November 2018, Committee for Medicinal Products for Human Use (CHMP) opinion; and March 2019, European Commission Decision) [7, 19]. Only a few studies have focused on such country-level dynamics of prescription rates of fluoroquinolones and factors influencing any changes. One study on German prescription data from community pharmacies found a significant downward trend also starting before the regulatory interventions [20]. Overall, decreases could be attributable to other factors influencing prescription behaviour such as antibiotic stewardships, or local changes in clinical guidance. Nevertheless, in our data, such decreases were of modest size, showing, at best, a reduction of prescriptions of around 25% in the UK; if any effect of regulatory interventions may have been obscured, the relevance of its effect was not supported by our data. Interestingly, in Spain, a decrease in prescriptions could be seen in the overall rates around March/April 2020, with a small increase in discontinuation rates and alternative antibiotic use rates. Although temporally related to the regulatory interventions more than 1 year earlier, this change coincided with the first wave of the coronavirus disease 2019 (COVID-19) pandemic hitting Western Europe. Considering the major changes due to the pandemic and the associated population-level interventions (e.g., dynamics of infectious diseases, or willingness and possibilities of visiting primary care physicians), this decrease of fluoroquinolone use and increase in alternative antibiotics in Spain was difficult to attribute to the regulatory interventions taken for fluoroquinolones. Further research may consider examining why, specifically in Spain, this time period was associated with drops in prescription rates of fluoroquinolones, or possibly overall antimicrobial prescriptions, and whether changes observed in Spain may have been driven by the COVID-19 pandemic changes. In Belgium, an absolute reduction as well as a reduction in seasonally fluctuating peaks in prescriptions was found to occur no later than the summer of 2018. This sudden drop was related to changes in reimbursement criteria of fluoroquinolones in Belgium. As of May 2018, fluoroquinolones, including ofloxacin, ciprofloxacin, norfloxacin, levofloxacin and moxifloxacin, are no longer reimbursed for the treatment of respiratory tract infections or uncomplicated urinary tract infections [21]. In the Netherlands, a drop in prescription rates in the regression analyses could be observed after implementation of regulatory interventions. However, the changes were, at best, modest and, for example, not reflected as breakpoints when modelling age-adjusted rates.

Several methodological considerations should be mentioned. First, we could not determine any potential impact of regulatory interventions on prescriptions in secondary care, including hospitals. Considering that hospitals include a higher density of healthcare professionals and may possess more professionalised or matured networks of disseminating safety information on medications, the impact of regulatory interventions may have been stronger or swifter there. Second, unknown indications were ranging from 37.7 to 94.1%. This may make our stratified analyses for indication, and estimates of ratio on/off-label, vulnerable to selection bias and accordingly introduce challenges in interpretation for these analyses. Moreover, our study included specific code lists and excluded symptom-related codes and general infection diagnoses codes, which may have led to an underestimation of the known indications in all the databases. Third, as data on medicine prescriptions did not equate to actual use, the algorithm for determining early discontinuation of fluoroquinolones may have underestimated true discontinuation. Vice versa, the early discontinuation proportion may have been overestimated due to the definition used (start of a new antibiotic before finishing the course of fluoroquinolone), as switching followed by early discontinuation might be actual add-on treatments. Fourth, it was not feasible to (manually) validate the automatic classification of key supporting variables in our retrospective data, e.g., indications for fluoroquinolone prescriptions, and, subsequently, classifications of on- or off-label use. Indications could only be indirectly identified using comprehensive code lists to classify indications on related data such as comorbidities. We could not exclude that missingness of information to classify indications may occur more often in persons where fluoroquinolone prescriptions truly changed across time. We used segmented regression methods to analyse time trends. This was a data-driven approach that allowed for seasonal trends to be observed if they occurred, but did not explicitly test for changes in fluoroquinolone use before and after regulatory intervention, or adjust for seasonality. This could be explored in further studies.

The strengths of our study included using a large number of patients per country, which increases precision to show any potential changes of prescriptions across time. Furthermore, use of the OMOP CDM increased comparability of results across countries. Lastly, findings seemed generalisable to the primary care situation in countries with a similar healthcare system where similar regulatory interventions were implemented.