Exploiting Real-World Data to Optimize the Use of Antibiotics

CDER-led research is helping us to use the information in electronic health records to advance the safe use of antibiotics.

The Scientific Challenge

In the treatment of infections, antibiotics have saved millions of lives. However, these drugs are also associated with well-known risks, such as rising rates of resistance in bacterial pathogens, negative impacts on the intestinal microbiome, and serious adverse events. Because each additional day of antibiotic therapy can increase the associated risks, it is critical that the treatment of common microbial infections be based on the safest and most effective administration and duration of antibiotic therapy. Through the National Action Plan for Combating Antibiotic-Resistant Bacteria (CARB), CDER has supported research at Johns Hopkins University School of Medicine to help us use the data in electronic health records to better understand the association between varying durations of antibiotic therapy and patient outcomes.

Gathering the Data Needed to Compare Antibiotic Treatment Regimens

Under the CARB Research Program, researchers have developed an automated approach for extracting patient-level data from Epic electronic health record software in five hospitals within the Johns Hopkins Health System. This novel approach enhances access to the multicenter data needed to capture clinical practice and patient experience, streamlines analyses, and defends against breeches of patient privacy. The accuracy of the electronically extracted data, pertaining to demographics, pre-existing medical conditions, severity of infection, source and source control measures, microbiological data, antibiotic treatment data, and clinical outcomes, was compared to the accuracy associated with manually collected data as assessed through an iterative process. Approximately 95% of the data elements needed to address study questions could be reliably captured using the automated extraction process.

Evaluating Antibiotic Dosing Regimens for Optimization Against Two Kinds of Bacterial Infection

The researchers used the data extracted from electronic health records to investigate antibiotic treatment optimization in two different contexts: 1) Pseudomonas aeruginosa bloodstream infections in adults and 2) pyelonephritis in children. P. aeruginosa can cause common and serious bloodstream infections, associated with significant morbidity and mortality, in patients with chronic medical conditions. Prolonged durations of antibiotic therapy have traditionally been prescribed to treat such bloodstream infection, but given the potential adverse consequences described above, Johns Hopkins investigators sought to determine if shorter courses of antibiotic therapy (i.e., < 10 days) might result in clinical outcomes similar to those seen in prolonged courses of therapy for adult patients with uncomplicated P. aeruginosa bloodstream infections.1

In their multicenter, observational, propensity-score weighted cohort of 249 adults with a positive blood culture for P. aeruginosa, the researchers found no difference in rates of death or recurrent infection within 30 days, regardless of whether patients were treated with a short course (median 9 days) or prolonged course (median 16 days) of antibiotics. Moreover, patients treated with shorter courses were, on average, discharged from the hospital approximately four days sooner than those who remained on longer courses of intravenous therapy.

In a second study, the research question focused on the treatment of children with pyelonephritis,2 which is an infection of the upper urinary tracts that can lead to both short-term and long-term morbidity, including sepsis, acute kidney injury, renal scarring, and chronic hypertension. To alleviate symptoms during the acute phase of the infection and reduce the potential for long-term consequences, pediatric guidelines recommend treating pyelonephritis with a total of 7 to 14 days of antibiotic therapy. Here again, the researchers questioned whether a shorter duration of treatment (7 days) might be as effective as the longer duration (14 days); if so, the researchers proposed, the shorter treatment time would be greatly preferred for its potential to reduce the likelihood of antibiotic-associated adverse events such as Clostridioides difficile infection, end-organ toxicity, hypersensitivity reactions, and a furthering of antibiotic resistance.

The second study examined 791 children, 6 months to 18 years of age, meeting laboratory and clinical criteria for pyelonephritis and evincing urine cultures positive for Escherichia coli, Klebsiella species, or Proteus mirabilis. The researchers in this study again found no difference in the odds of patients developing subsequent urinary tract infections within 30 days after completing a short course (< 10 days) of antibiotic treatment as compared to patients having completed a prolonged course (> 10 days) of treatment, although there was a trend toward fewer post-treatment drug-resistant urinary tract infections in the short-course group. Thus, in two distinct contexts of infectious disease—one in adult patients and one in children—short courses of antibiotic therapy appeared to be as effective as prolonged courses of treatment, thereby suggesting that careful investigation of treatment durations may offer a means for mitigating the risk for developing antibiotic-resistant bacterial strains.

Future Directions

The approaches used in these studies for extracting patient data to compare treatment outcomes in real-world settings promise to assist FDA in future efforts to analyze large clinical databases. For example, an electronic extraction technique similar to the one described here could be used to extract data from a large number of hospitals to evaluate the clinical outcomes of patients with rare bacterial infections or to monitor antibiotic-associated adverse drug events. The further development of a network of participating institutions could enhance FDA’s efforts to analyze large collections of clinical data to optimize the safe administration of anti-infective therapies.

How can this work improve patient safety?

These two research studies demonstrated the feasibility and advantages of a novel automated approach for extracting patient-level data from electronic health records to capture treatment outcomes in diverse real-world health care settings. The results provide valuable evidence to inform best practices related to the duration of antibiotic treatment in diverse bacterial infections, optimizing patient outcomes while reducing the risk for antimicrobial resistance.

Literature Cited

1Fabre V, Amoah J, Cosgrove SE, Tamma PD. Antibiotic Therapy for Pseudomonas aeruginosa Bloodstream Infections: How Long Is Long Enough? Clin Infect Dis. 2019 Nov 13;69(11):2011-2014. doi: 10.1093/cid/ciz223. PMID: 30882137; PMCID: PMC7320076.
2Fox MT, Amoah J, Hsu AJ, Herzke CA, Gerber JS, Tamma PD. Comparative Effectiveness of Antibiotic Treatment Duration in Children With Pyelonephritis. JAMA Netw Open. 2020 May 1;3(5):e203951. doi: 10.1001/jamanetworkopen.2020.3951. PMID: 32364593; PMCID: PMC7199115.