Lopes, Guilherme S.

Abstract Purpose Traditional adverse event (AE) reporting in oncology trials focuses on the single worst CTCAE grade, which may underrepresent chronic or recurrent toxicity burden. We applied a longitudinal toxicity framework to compare toxicity profiles of chemotherapy with or without cetuximab in metastatic colorectal cancer. Patients and Methods We pooled two randomized first-line trials in the ARCAD database. AEs examined were diarrhea, rash, hand-foot syndrome (HFS), fatigue, anorexia, and mucositis. Outcomes included grade ≥3 AE, time to first occurrence of maximum grade, early onset (≤6 weeks), and AEL, a normalized measure of cumulative toxicity burden over treatment. Analyses were adjusted for chemotherapy backbone, ECOG performance status, sex, primary tumor location, dose reduction, and treatment duration. Results Compared with Chemotherapy alone (n = 564), Chemotherapy plus cetuximab (n = 738) was associated with higher grade ≥3 rash (21% vs 0.5%; adjusted odds ratio [OR] 49.89, 95% CI 15.8–157.4), higher rash AEL (0.257 vs 0.069; adjusted mean difference 0.22, 95% CI 0.21–0.23), and more frequent early-onset maximum rash (67% vs 34%; adjusted OR 4.28, 95% CI 2.72–6.74). Rash AEL remained higher with cetuximab within maximum-grade strata. HFS showed higher grade ≥3 risk and overall AEL with cetuximab, but no within-grade AEL difference, indicating higher overall HFS burden reflected grade distribution rather than within-grade chronicity. No consistent differences were observed for other AEs. Conclusions Incorporating onset timing and AEL distinguished persistent toxicity burden from isolated peak events. This framework may support comparative tolerability assessment when chronic toxicity burden is central to decision-making.

Objectives Sex as a biological variable affects response to opioids. However, few reports describe the prevalence of specific adverse reactions to commonly prescribed opioids in men and women separately. A large cohort was used to investigate sex differences in type and occurrence of adverse reactions associated with use of codeine, tramadol, oxycodone and hydrocodone. Design Retrospective cohort study. Setting Participants in the Right Drug, Right Dose, Right Time (RIGHT) Study. Participants The medical records of 8457 participants in the RIGHT Study who received an opioid prescription between 1 January 2004 and 31 December 2017 were reviewed 61% women, 94% white, median age (Q1–Q3)=58 (47–66). Primary and secondary outcome measures Adverse reactions including gastrointestinal, skin, psychiatric and nervous system issues were collected from the allergy section of each patient’s medical record. Sex differences in the risk of adverse reactions due to prescribed opioids were modelled using logistic regression adjusted for age, body mass index, race and ethnicity. Results From 8457 participants (of which 449 (5.3%) reported adverse reactions), more women (6.5%) than men (3.4%) reported adverse reactions to at least one opioid (OR (95% CI)=2.3 (1.8 to 2.8), p<0.001). Women were more likely to report adverse reactions to tramadol (OR (95% CI)=2.8 (1.8 to 4.4), p<0.001) and oxycodone (OR (95% CI)=2.2 (1.7 to 2.9), p<0.001). Women were more likely to report gastrointestinal (OR (95% CI)=3.1 (2.3 to 4.3), p<0.001), skin (OR (95% CI)=2.1 (1.4 to 3.3), p=0.001) and nervous system issues (OR (95% CI)=2.3 (1.3 to 4.2), p=0.004). Conclusions These findings support the importance of sex as a biological variable to be factored into pain management studies.

Abstract Background Delirium is underdiagnosed in clinical practice and is not routinely coded for billing. Manual chart review can be used to identify the occurrence of delirium; however, it is labor-intensive and impractical for large-scale studies. Natural language processing (NLP) has the capability to process raw text in electronic health records (EHRs) and determine the meaning of the information. We developed and validated NLP algorithms to automatically identify the occurrence of delirium from EHRs. Methods This study used a randomly selected cohort from the population-based Mayo Clinic Biobank (N = 300, age ≥65). We adopted the standardized evidence-based framework confusion assessment method (CAM) to develop and evaluate NLP algorithms to identify the occurrence of delirium using clinical notes in EHRs. Two NLP algorithms were developed based on CAM criteria: one based on the original CAM (NLP-CAM; delirium vs no delirium) and another based on our modified CAM (NLP-mCAM; definite, possible, and no delirium). The sensitivity, specificity, and accuracy were used for concordance in delirium status between NLP algorithms and manual chart review as the gold standard. The prevalence of delirium cases was examined using International Classification of Diseases, 9th Revision (ICD-9), NLP-CAM, and NLP-mCAM. Results NLP-CAM demonstrated a sensitivity, specificity, and accuracy of 0.919, 1.000, and 0.967, respectively. NLP-mCAM demonstrated sensitivity, specificity, and accuracy of 0.827, 0.913, and 0.827, respectively. The prevalence analysis of delirium showed that the NLP-CAM algorithm identified 12 651 (9.4%) delirium patients, the NLP-mCAM algorithm identified 20 611 (15.3%) definite delirium cases, and 10 762 (8.0%) possible cases. Conclusions NLP algorithms based on the standardized evidence-based CAM framework demonstrated high performance in delineating delirium status in an expeditious and cost-effective manner.

Background Current adverse event reporting practices do not document longitudinal characteristics of adverse effects, and alternative methods are not easily interpretable and have not been employed by clinical trials. Introducing time parameters in the evaluation of safety that are comprehensive yet easily interpretable could allow for a better understanding of treatment quality. In this study, we developed and applied a novel adverse event reporting method based on longitudinal adverse event changes to aid describing, summarizing, and presenting adverse event profile. We termed it the “Adverse Event Load, Onset, and Maximum Grade” method. Methods We developed two adverse event summary metrics to complement the traditional maximum grade report. Onset time indicates the time period in which the maximum grade for a specific adverse event occurred and was defined as “early” (i.e. maximum grade happened for the first time before 6 weeks) or “late” (i.e. after the 6 th week). Adverse event load indicates the overall severity of a specific adverse event over the entire treatment. Higher adverse event load indicates a worse overall experience. These metrics can be calculated for adverse events with different maximum grades, in treatments with planned changes (e.g. dosage changes), using data sets with different number of adverse event data points between treatments (e.g. treatments with longer cycle lengths may have less adverse event data points) and on data sets with different adverse event data availability (e.g. cycle basis and patient-outcome reports). We tested the utility of this method using individual patient data from two major backbone therapies (“Irinotecan” and “Oxaliplatin”) from the N9741 trial available in the Fondation ARCAD database ( fondationarcad.org ). We investigated profiles of diarrhea, neutropenia/leukopenia, and nausea/vomiting. Results Our method provided additional information compared to traditional adverse event reports. For example, for nausea/vomiting, while patients in Irinotecan had a higher risk of experiencing maximum grade 3–4 (15.6% vs 7.6%, respectively; p < 0.001), patients in both groups experienced similar severity over time (adverse effect load = 0.102 and 0.096, respectively; p = 0.26), suggesting that patients in Oxaliplatin experienced a lower-grade but more persistent nausea/vomiting. For neutropenia/leukopenia, more patients in Irinotecan experienced their maximum grade for the first time early in the treatment compared to patients in Oxaliplatin (67.9% vs 41.7%; p < 0.001), regardless of maximum grade. Longitudinal information can help compare treatments or guide clinicians on choosing appropriate interventions for low-grade but persistent adverse event or early adverse event onset. Conclusion We developed an adverse event reporting method that provides clinically relevant information about treatment toxicity by incorporating two longitudinal adverse event metrics to the traditional maximum grade approach. Future research should establish clinical benchmarks for metrics included in this adverse event reporting method.

Background Opioid analgesics are among the most commonly prescribed medications in the United States. Opioids are useful in the management of pain, but their use can also adversely affect patients. However, studies reporting patterns of adverse events due to use of opioid analgesics in men and women are still scarce. Understanding the individual characteristics affecting response to opioids may allow clinicians to better individualize treatments. In this study, we investigated sex differences in the patterns of adverse events as a result of opioid use. Methods We used data from 8,457 patients participating in the Mayo Clinic Biobank “Right Drug, Right Dose, Right Time (RIGHT protocol)” study of pre‐emptive genotyping who were prescribed at least one of four opioid medications (codeine, tramadol, hydrocodone, or oxycodone) between 01/01/2004 and 12/31/2017. Adverse events due to use of these medications were collected from the allergy section in each patient’s electronical medical record, and were organized into four Medical Dictionary for Regulatory Activities (MedDRA) categories: gastrointestinal (e.g. nausea, vomiting), skin and subcutaneous tissue (e.g. rash, itching), psychiatric (e.g. anxiety, hallucinations), and nervous system (e.g. headache, dizziness). We modeled sex differences in the risk of adverse events by each opioid, and sex differences in the risk of each adverse event due to any opioid using logistic regression adjusted for age, race, ethnicity, and body mass index (BMI). Results Participants with at least one opioid prescription were 60.8% female, mostly white (94.2%) and non‐Hispanic (98.9%). Women (relative to men) were younger (median = 61.6 vs. 69.1, respectively), had lower BMI (median = 27.4 vs. 28.9), and were prescribed more codeine (18.8% vs. 15.5%). Overall, 456 (5.4%) persons had a note in the allergy section of their medical record indicating a problem with an opioid medication. Women were more likely than men to have a note in the allergy section referring to at least one opioid (6.6% and 3.5%, respectively; p < 0.001). In addition, among participants who had at least one note related to opioid use in their allergy section, women were more likely to have notes regarding gastrointestinal complications (OR [95% CI] = 2.07 [1.3 – 3.2], p = 0.002), but less likely to have notes regarding psychiatric issues (OR [95% CI] = 0.30 [0.2 – 0.5], p < 0.001). Conclusion Women were more likely than men to experience adverse events due to use of codeine, tramadol, hydrocodone, and oxycodone. In addition, the types of adverse reactions differed between men and women. These data suggest that further studies are needed to ensure that both men and women have optimal responses to opioid medications. Support or Funding Information This work was supported by the Mayo Clinic Specialized Center of Research Excellent on Sex Differences, the Mayo Clinic Center for Individualized Medicine, the Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, and the National Institutes of Health grants [U19 GM61388 (The Pharmacogenomics Research Network), R01 GM28157, U01 HG005137, R01 GM125633, R01 AG034676 (The Rochester Epidemiology Project)], and [U01 HG06379 and U01 HG06379 Supplement (The Electronic Medical Record and Genomics (eMERGE) Network)].

AbstractObjectiveWe aimed to test for an association between the amount of circulating fetal cell‐free DNA and trisomy, and whether NIPS failure due to low fetal fraction indicates trisomy risk.MethodMaternal BMI, maternal age, fetal sex, gestational age, fetal cfDNA fraction, and NIPS results was collected on 2374 pregnancies. Additional clinical information was available for 1180 research consented patients. We investigated associations between fetal fraction and available variables and determined the success rate of repeat NIPS testing.ResultsFetal trisomy was marginally associated with decreased fetal fraction (P = .067). However, the proportions of trisomy events were not significantly increased in women who had failed NIPS due to low fetal fraction (<4%) (OR = 1.37 [0.3‐7.4]; P = .714). 66% of repeated NIPS after a second blood draw were successful.ConclusionFailure to meet the clinical cutoff of 4% fetal fraction established for NIPS accuracy did not suggest increased risk for trisomy in our cohort. Because repeat testing was successful in the majority of cases and most failures were explained by high BMI and low gestational age, a redraw may be an appropriate next step before invasive screening due to concerns for trisomic pregnancies.