A descriptive analysis of postmarketing requirement studies and clinical trials.

PURPOSE: Under the Food and Drug Administration Amendments Act of 2007 (FDAAA), the FDA has the authority to require applicants to conduct postmarketing studies or clinical trials. These postmarketing requirements (PMRs) provide additional data on the safety of the drug product. The purpose of the study was to conduct a descriptive analysis of FDAAA PMRs and the resulting regulatory actions. METHODS: This study evaluated FDAAA PMRs established between 2013 and 2019. We used the Medical Dictionary for Regulatory Activities (MedDRA) to map preferred terms (PTs) for serious risks associated with the PMRs. Relevant documents available in the FDA's document archiving, reporting, and regulatory tracking system (DARRTS), including but not limited to internal letters and reviews, documents submitted by applicants, and publicly available data sources were assessed for data collection of study elements. RESULTS: Of the 1079 new FDAAA PMRs established between January 01, 2013, and December 31, 2019, 82% (n = 884) were associated with new drug applications (NDAs) and 18% (n = 195) with biologic license applications (BLAs). Most PMRs were established at the time of drug approval (73%, n = 789) compared to post-approval (27%, n = 290). The majority of PMRs had an open status (59%, n = 639) and 41% (n = 440) were closed. The median time from the PMR establishment date to submission of the results to the FDA was 690 days (interquartile range [IQR]: 748 days) for 167 completed clinical trials and 483 days (IQR: 603 days) for 241 completed studies. Approximately 53% (180/339) of fulfilled FDAAA PMRs resulted in labeling changes. CONCLUSIONS: FDAAA PMRs are useful in informing postmarket safety of drugs. Most FDAAA PMRs were established at the time of drug approval, reflecting safety signals identified during the review of the marketing application, and over half of fulfilled FDAAA PMRs resulted in regulatory action.

Validation of diagnosis codes to identify hospitalized COVID-19 patients in health care claims data.

PURPOSE: Health plan claims may provide complete longitudinal data for timely, real-world population-level COVID-19 assessment. However, these data often lack laboratory results, the standard for COVID-19 diagnosis. METHODS: We assessed the validity of ICD-10-CM diagnosis codes for identifying patients hospitalized with COVID-19 in U.S. claims databases, compared to linked laboratory results, among six Food and Drug Administration Sentinel System data partners (two large national insurers, four integrated delivery systems) from February 20-October 17, 2020. We identified patients hospitalized with COVID-19 according to five ICD-10-CM diagnosis code-based algorithms, which included combinations of codes U07.1, B97.29, general coronavirus codes, and diagnosis codes for severe symptoms. We calculated the positive predictive value (PPV) and sensitivity of each algorithm relative to laboratory test results. We stratified results by data source type and across three time periods: February 20-March 31 (Time A), April 1-30 (Time B), May 1-October 17 (Time C). RESULTS: The five algorithms identified between 34 806 and 47 293 patients across the study periods; 23% with known laboratory results contributed to PPV calculations. PPVs were high and similar across algorithms. PPV of U07.1 alone was stable around 93% for integrated delivery systems, but declined over time from 93% to 70% among national insurers. Overall PPV of U07.1 across all data partners was 94.1% (95% CI, 92.3%-95.5%) in Time A and 81.2% (95% CI, 80.1%-82.2%) in Time C. Sensitivity was consistent across algorithms and over time, at 94.9% (95% CI, 94.2%-95.5%). CONCLUSION: Our results support the use of code U07.1 to identify hospitalized COVID-19 patients in U.S. claims data.

Neutralizing and Neuraminidase Antibodies Correlate With Protection Against Influenza During a Late Season A/H3N2 Outbreak Among Unvaccinated Military Recruits.

BACKGROUND: Antibodies that inhibit hemagglutination have long been considered a correlate of protection against influenza, but these antibodies are only a subset of potentially protective antibodies. Neutralizing and neuraminidase antibodies may also contribute to protection, but data on their associations with protection are limited. METHODS: We measured preoutbreak hemagglutinin pseudovirus neutralization (PVN) and neuraminidase inhibition (NAI) antibody titers in unvaccinated military recruits who experienced an H3N2 influenza outbreak during training. We conducted a case-control study to investigate the association between titers and protection against influenza illness or H3N2-associated pneumonia using logistic regression. RESULTS: With every 2-fold increase in PVN titer, the odds of medically attended polymerase chain reaction-confirmed H3N2 infection (H3N2+) decreased by 41% (odds ratio [OR], 0.59; 95% confidence interval [CI], .45 to .77; P < .001). Among those who were H3N2+, the odds for pneumonia decreased by 52% (OR, 0.48; CI, .25 to .91; P = .0249). With every 2-fold increase in NAI titer, the odds of medically attended H3N2 infection decreased by 32% (OR, 0.68; 95% CI, .53 to .87; P = .0028), but there was no association between NAI titers and H3N2-associated pneumonia. There was also no synergistic effect of PVN and NAI antibodies. CONCLUSIONS: PVN and NAI titers were independently associated with reduced risk of influenza illness. NAI titers associated with protection had greater breadth of reactivity to drifted strains than PVN titers. These findings show that PVN and NAI titers are valuable biomarkers for assessing the odds of influenza infection.

Age-dependent distribution of periodontitis in two countries: Findings from NHANES 2009 to 2014 and SHIP-TREND 2008 to 2012.

OBJECTIVE: We used epidemiologic data of clinical periodontal status from two population-based samples in two countries, United States and Germany, to examine 1) the impact of age on the relative contribution of recession and pocketing on the distribution of clinical attachment loss, and 2) whether it is feasible to define age-dependent thresholds for severe periodontitis. METHODS: The analytical sample was based on persons aged ≥30 and included 10,713 individuals in the United States, participants in NHANES 2009 to 2014, and 3,071 individuals in Pomerania, Germany, participants in the SHIP-Trend 2008 to 2012. NHANES used a full-mouth examination protocol to collect data on recession (R), pocket depth (PD) and clinical attachment loss (CAL) for six sites/tooth on a maximum of 28 teeth; SHIP-Trend used a half-mouth examination at four sites/tooth. In both samples, percentile distributions of mean CAL/person were generated for each 5-year age interval. Age-dependent thresholds defining the upper quintile of mean CAL were calculated for both samples. The topographic intraoral distribution of CAL and the relative contribution of R and PD on CAL was assessed. RESULTS: Mean CAL increased linearly with age in both samples and was higher in SHIP-Trend than NHANES across the age spectrum. In contrast, mean PD was constant across age groups in both populations. R contributed increasingly to CAL with age, especially after 45 to 49 years. Upper quintile mean CAL thresholds in NHANES were < 3 mm for ages up to 39 years, and under 3.58 mm in all other age groups. Corresponding values in SHIP-Trend were also < 3 mm in ages up to 39 years but increased linearly with age up to 7.21 mm for ages ≥75 years. CONCLUSIONS: Despite substantial differences in the overall severity of attachment loss between the two samples, common patterns of CAL and of the relative contribution of R and PD to CAL with increasing age were identified. Although periodontitis severity may vary in different populations, empirical evidence-driven definitions of CAL thresholds signifying disproportionate severity of periodontitis by age are feasible.

Algorithmic Identification of Treatment-Emergent Adverse Events From Clinical Notes Using Large Language Models: A Pilot Study in Inflammatory Bowel Disease.

Outpatient clinical notes are a rich source of information regarding drug safety. However, data in these notes are currently underutilized for pharmacovigilance due to methodological limitations in text mining. Large language models (LLMs) like Bidirectional Encoder Representations from Transformers (BERT) have shown progress in a range of natural language processing tasks but have not yet been evaluated on adverse event (AE) detection. We adapted a new clinical LLM, University of California - San Francisco (UCSF)-BERT, to identify serious AEs (SAEs) occurring after treatment with a non-steroid immunosuppressant for inflammatory bowel disease (IBD). We compared this model to other language models that have previously been applied to AE detection. We annotated 928 outpatient IBD notes corresponding to 928 individual patients with IBD for all SAE-associated hospitalizations occurring after treatment with a non-steroid immunosuppressant. These notes contained 703 SAEs in total, the most common of which was failure of intended efficacy. Out of eight candidate models, UCSF-BERT achieved the highest numerical performance on identifying drug-SAE pairs from this corpus (accuracy 88-92%, macro F1 61-68%), with 5-10% greater accuracy than previously published models. UCSF-BERT was significantly superior at identifying hospitalization events emergent to medication use (P < 0.01). LLMs like UCSF-BERT achieve numerically superior accuracy on the challenging task of SAE detection from clinical notes compared with prior methods. Future work is needed to adapt this methodology to improve model performance and evaluation using multicenter data and newer architectures like Generative pre-trained transformer (GPT). Our findings support the potential value of using large language models to enhance pharmacovigilance.

Algorithmic identification of treatment-emergent adverse events from clinical notes using large language models: a pilot study in inflammatory bowel disease.

Background and Aims: Outpatient clinical notes are a rich source of information regarding drug safety. However, data in these notes are currently underutilized for pharmacovigilance due to methodological limitations in text mining. Large language models (LLM) like BERT have shown progress in a range of natural language processing tasks but have not yet been evaluated on adverse event detection. Methods: We adapted a new clinical LLM, UCSF BERT, to identify serious adverse events (SAEs) occurring after treatment with a non-steroid immunosuppressant for inflammatory bowel disease (IBD). We compared this model to other language models that have previously been applied to AE detection. Results: We annotated 928 outpatient IBD notes corresponding to 928 individual IBD patients for all SAE-associated hospitalizations occurring after treatment with a non-steroid immunosuppressant. These notes contained 703 SAEs in total, the most common of which was failure of intended efficacy. Out of 8 candidate models, UCSF BERT achieved the highest numerical performance on identifying drug-SAE pairs from this corpus (accuracy 88-92%, macro F1 61-68%), with 5-10% greater accuracy than previously published models. UCSF BERT was significantly superior at identifying hospitalization events emergent to medication use (p < 0.01). Conclusions: LLMs like UCSF BERT achieve numerically superior accuracy on the challenging task of SAE detection from clinical notes compared to prior methods. Future work is needed to adapt this methodology to improve model performance and evaluation using multi-center data and newer architectures like GPT. Our findings support the potential value of using large language models to enhance pharmacovigilance.

Data visualization of the relationship between smoking and periodontal site-specific effects across the lifespan in the US adult population.

BACKGROUND: Data visualization techniques were used to ascertain (1) site-specific effects of cigarette smoking on the periodontium compared to never-smokers; (2) patterns of site-specific effects by age among current and never-smokers using contour maps. METHODS: Data from 10,713 dentate participants aged ≥30 years in NHANES 2009-2014 were used. Pocket depth (PD) and clinical attachment level (CAL) for six sites/tooth were ascertained by smoking status and plotted using contour maps to identify new patterns. RESULTS: In the overall sample, 19% (n = 2015) were current smokers and 56% (n = 6013) were never-smokers. Contour maps of the overall sample showed teeth/sites most affected with mean PD > 2.1 mm were molars (2,3,15,18,19,30,31) in mesio-lingual (ML) and disto-lingual (DL) sites. Most affected sites for current smokers were interproximal sites of most posterior teeth. Among never-smokers, fewer teeth/sites were affected with PD > 2.1 mm, whereas among smokers, number of affected teeth/sites increased with age. Overall, teeth/sites most affected with mean CAL≥2.1 mm were noted in 2,3(ML), 3(DL), 14(DF, DL), 15(MF, ML), 18(ML), 19(DL, ML), and 30-31(ML, DL) with upper anterior teeth least affected. Among current smokers, several teeth/sites were affected (CAL≥2.1 mm): 2,3(all six sites), 4(ML, DL), 9(ML), 11-21(DL), 13-18(DF, ML, MIL, DL), 19-20(DF, ML, MIL), 14-18(MIF), 21(MIF, ML, DL), 22(MF), 23-27(MIL), 24-26(MIL, MF, DF in 26), 27(MF), 28(MF, ML, DL), 29-31(all 6 sites except MIF 30,31). As age increased, more teeth/sites were affected among smokers and by the 5th decade nearly all teeth/sites had CAL≥2.0 mm. CONCLUSIONS: Contour mapping identifies patterns and dramatically visualizes the substantial periodontal site-specific differences. Current smokers had more affected teeth and/or periodontal sites with a different contour pattern than never-smokers.

Age-dependent distribution of periodontitis in two countries: Findings from NHANES 2009 to 2014 and SHIP-TREND 2008 to 2012.

OBJECTIVE: We used epidemiologic data of clinical periodontal status from two population-based samples in two countries, United States and Germany, to examine 1) the impact of age on the relative contribution of recession and pocketing on the distribution of clinical attachment loss, and 2) whether it is feasible to define age-dependent thresholds for severe periodontitis. METHODS: The analytical sample was based on persons aged ≥30 and included 10,713 individuals in the United States, participants in NHANES 2009 to 2014, and 3,071 individuals in Pomerania, Germany, participants in the SHIP-Trend 2008 to 2012. NHANES used a full-mouth examination protocol to collect data on recession (R), pocket depth (PD) and clinical attachment loss (CAL) for six sites/tooth on a maximum of 28 teeth; SHIP-Trend used a half-mouth examination at four sites/tooth. In both samples, percentile distributions of mean CAL/person were generated for each 5-year age interval. Age-dependent thresholds defining the upper quintile of mean CAL were calculated for both samples. The topographic intraoral distribution of CAL and the relative contribution of R and PD on CAL was assessed. RESULTS: Mean CAL increased linearly with age in both samples and was higher in SHIP-Trend than NHANES across the age spectrum. In contrast, mean PD was constant across age groups in both populations. R contributed increasingly to CAL with age, especially after 45 to 49 years. Upper quintile mean CAL thresholds in NHANES were < 3 mm for ages up to 39 years, and under 3.58 mm in all other age groups. Corresponding values in SHIP-Trend were also < 3 mm in ages up to 39 years but increased linearly with age up to 7.21 mm for ages ≥75 years. CONCLUSIONS: Despite substantial differences in the overall severity of attachment loss between the two samples, common patterns of CAL and of the relative contribution of R and PD to CAL with increasing age were identified. Although periodontitis severity may vary in different populations, empirical evidence-driven definitions of CAL thresholds signifying disproportionate severity of periodontitis by age are feasible.

Global Burden of Neonatal Invasive Pneumococcal Disease: A Systematic Review and Meta-analysis.

BACKGROUND: This study aimed to estimate the global burden of invasive pneumococcal disease (IPD) incidence among neonates during the pre-pneumococcal conjugate vaccine era. METHODS: A systematic search of published and unpublished data was undertaken. Bias assessment and qualitative synthesis of the included studies were carried out. Random effects models using the method of DerSimonian and Laird were constructed. Subgroup analyses, sensitivity analyses and meta-influence analysis were undertaken. Sources of heterogeneity were investigated. RESULTS: From 26 neonatal IPD data points in the pre-pneumococcal conjugate vaccine era, the overall pooled neonatal IPD incidence, in the general population, combining all 3 United Nations (UN) country strata was estimated to be 36.0 per 100,000 live births [95% confidence interval (CI): 20.0-64.7 per 100,000]. The pooled neonatal IPD incidence in the general population in the less-developed UN country strata was estimated to be 16.0 per 100,000 live births (95% CI: 3.9-65.6 per 100,000) and in the more-developed stratum was 41.1 per 100,000 live births (95% CI: 29.1-58.1 per 100,000). This counter-intuitive finding is likely to have been affected by data quantity and confounding by time. A pooled estimate for the least-developed stratum was not computable as there was only 1 study in this stratum-a study from The Gambia with an unweighted IPD incidence of 369.5 per 100,000 (95% CI: 119.2-1138.5 per 100,000). CONCLUSIONS: Pneumococcus was a recognized pathogen among neonates in all development regions of the world. The burden of neonatal IPD, particularly in the least-developed UN country stratum, requires substantial further evaluation.

Significance and Implications of Patient-reported Xerostomia in Sjögren's Syndrome: Findings From the National Institutes of Health Cohort.

BACKGROUND: Xerostomia is a chief complaint of patients with Sjögren's syndrome (SS). However, newer proposals for SS classification remove xerostomia and hyposalivation from the criteria list. Given these developments and the importance of patient-centered research outcomes, we sought to evaluate the utility of patient-reported xerostomia with implications for classification criteria, and clinical trials targeting SS treatment modalities. METHODS: A nested case-control study was designed within The National Institute of Dental and Craniofacial Research/National Institutes of Health (NIDCR/NIH) SS Cohort - one of the largest SS cohorts in the US. Clinical characteristics of those with and without xerostomia in SS and other salivary gland dysfunctions were compared. Several analytical methods were employed, including multivariable logistic regression modeling. FINDINGS: The NIDCR/NIH Sjögren's Syndrome Clinic has an open cohort with ongoing enrollment since 1984. This open cohort comprised of 2046 participants by August 27, 2015. Baseline data of 701 SS, 355 Sicca, and 247 ISS participants within the source cohort were analyzed. Xerostomia was highest among SS participants (87.4%, 95% CI: 84.8%-89.8%) compared to Sicca (72.4%, 95% CI: 67.4%-77.0%, p<0.001) and ISS groups (38.1%, 95% CI: 32.0%-44.4%, p<0.001). Those with xerostomia were more likely to have SS than Sicca/ISS (OR=4.98, 95% CI: 3.78-6.56). The ability of xerostomia to screen for SS among those with salivary gland dysfunction was higher than screening for Sicca/ISS. Screening diagnostics of xerostomia were of greater utility compared to hyposalivation. After adjusting for confounding in multivariable modeling, SS participants with xerostomia were more likely to be White (Black/African Americans (OR: 0.40, 95% CI: 0.23-0.68, p-value=0.001) and Asians (OR: 0.49, 95% CI: 0.25-0.96, p-value=0.038) were less likely to have xerostomia compared to Whites), have dry eye symptoms for >3months (OR: 5.80, 95% CI: 3.62-9.28, p-value <0.001), a lower Van Bijsterveld score (OR: 0.55, 95%CI: 0.34-0.90, p-value=0.017), a lower stimulated salivary flow rate (OR: 1.67, 95% CI: 1.06-2.65, p-value=0.028), a focus score of >2 (OR: 1.92, 95% CI: 1.20-3.09, p-value=0.007), and salivary gland swelling (OR: 49.39, 95% CI: 2.02-1206.30, p-value=0.017). Age, gender, fatigue, pain, anxiety, and autoantibodies were not significantly associated with xerostomia. INTERPRETATION: Findings from this study indicate that patient-reported xerostomia is highly prevalent among SS patients and is associated with several clinical phenotypes of this complex syndrome, thereby making it an important indicator of SS. The evidence also suggests that xerostomia is not limited to low salivary flow but might be reflective of compositional changes of saliva. Consequently, these findings suggest the need to consider xerostomia in the development of SS classification criteria and in patient-centered outcomes research in SS intervention trials. This research was supported by the Intramural Research Program of the National Institutes of Health (NIH), National Institute of Dental and Craniofacial Research (NIDCR) Grant # DE000704-15. Dr. Baer is supported by RO1-DE-12354-15A1.