Development of a bayesian toxo-equivalence model between docetaxel and paclitaxel.

Members of the taxane class of chemotherapies, staples of cancer treatment since the 1990s, can induce chemotherapy-induced peripheral neuropathy (CIPN), a potentially irreversible outcome related to cumulative exposure. Switching between taxanes is often clinically necessary; however, different taxanes have different efficacies, toxicities, and dosing strategies, necessitating an evidence-based schema focused on toxicity. We performed a systematic review and meta-analysis of the literature on docetaxel and paclitaxel, extracting cumulative dose, rates of CIPN, and subject demographics, thereby establishing their dose-toxo-equivalence relationship through a Bayesian meta-analysis model, calculating doses of the two drugs that are expected to have comparable rates of CIPN, along with credible intervals. Our final model, based on 169 studies, produces credible interval widths that provide guidance within one treatment cycle. In practice, this model provides a framework under which oncologists can make treatment switching and dosing decisions, hopefully reducing patient risk of CIPN.

Assessment of a Naloxone Coprescribing Alert for Patients at Risk of Opioid Overdose: A Quality Improvement Project.

BACKGROUND: Patients taking high doses of opioids, or taking opioids in combination with other central nervous system depressants, are at increased risk of opioid overdose. Coprescribing the opioid-reversal agent naloxone is an essential safety measure, recommended by the surgeon general, but the rate of naloxone coprescribing is low. Therefore, we set out to determine whether a targeted clinical decision support alert could increase the rate of naloxone coprescribing. METHODS: We conducted a before-after study from January 2019 to April 2021 at a large academic health system in the Southeast. We developed a targeted point of care decision support notification in the electronic health record to suggest ordering naloxone for patients who have a high risk of opioid overdose based on a high morphine equivalent daily dose (MEDD) ≥90 mg, concomitant benzodiazepine prescription, or a history of opioid use disorder or opioid overdose. We measured the rate of outpatient naloxone prescribing as our primary measure. A multivariable logistic regression model with robust variance to adjust for prescriptions within the same prescriber was implemented to estimate the association between alerts and naloxone coprescribing. RESULTS: The baseline naloxone coprescribing rate in 2019 was 0.28 (95% confidence interval [CI], 0.24-0.31) naloxone prescriptions per 100 opioid prescriptions. After alert implementation, the naloxone coprescribing rate increased to 4.51 (95% CI, 4.33-4.68) naloxone prescriptions per 100 opioid prescriptions (P < .001). The adjusted odds of naloxone coprescribing after alert implementation were approximately 28 times those during the baseline period (95% CI, 15-52). CONCLUSIONS: A targeted decision support alert for patients at risk for opioid overdose significantly increased the rate of naloxone coprescribing and was relatively easy to build.

Pop-out search instigates beta-gated feature selectivity enhancement across V4 layers.

Visual search is a workhorse for investigating how attention interacts with processing of sensory information. Attentional selection has been linked to altered cortical sensory responses and feature preferences (i.e., tuning). However, attentional modulation of feature selectivity during search is largely unexplored. Here we map the spatiotemporal profile of feature selectivity during singleton search. Monkeys performed a search where a pop-out feature determined the target of attention. We recorded laminar neural responses from visual area V4. We first identified "feature columns" which showed preference for individual colors. In the unattended condition, feature columns were significantly more selective in superficial relative to middle and deep layers. Attending a stimulus increased selectivity in all layers but not equally. Feature selectivity increased most in the deep layers, leading to higher selectivity in extragranular layers as compared to the middle layer. This attention-induced enhancement was rhythmically gated in phase with the beta-band local field potential. Beta power dominated both extragranular laminar compartments, but current source density analysis pointed to an origin in superficial layers, specifically. While beta-band power was present regardless of attentional state, feature selectivity was only gated by beta in the attended condition. Neither the beta oscillation nor its gating of feature selectivity varied with microsaccade production. Importantly, beta modulation of neural activity predicted response times, suggesting a direct link between attentional gating and behavioral output. Together, these findings suggest beta-range synaptic activation in V4's superficial layers rhythmically gates attentional enhancement of feature tuning in a way that affects the speed of attentional selection.

Imprecision and Preferences in Interpretation of Verbal Probabilities in Health: a Systematic Review.

INTRODUCTION: Many health providers and communicators who are concerned that patients will not understand numbers instead use verbal probabilities (e.g., terms such as "rare" or "common") to convey the gist of a health message. OBJECTIVE: To assess patient interpretation of and preferences for verbal probability information in health contexts. METHODS: We conducted a systematic review of literature published through September 2020. Original studies conducted in English with samples representative of lay populations were included if they assessed health-related information and elicited either (a) numerical estimates of verbal probability terms or (b) preferences for verbal vs. quantitative risk information. RESULTS: We identified 33 original studies that referenced 145 verbal probability terms, 45 of which were included in at least two studies and 19 in three or more. Numerical interpretations of each verbal term were extremely variable. For example, average interpretations of the term "rare" ranged from 7 to 21%, and for "common," the range was 34 to 71%. In a subset of 9 studies, lay estimates of verbal probability terms were far higher than the standard interpretations established by the European Commission for drug labels. In 10 of 12 samples where preferences were elicited, most participants preferred numerical information, alone or in combination with verbal labels. CONCLUSION: Numerical interpretation of verbal probabilities is extremely variable and does not correspond well to the numerical probabilities established by expert panels. Most patients appear to prefer quantitative risk information, alone or in combination with verbal labels. Health professionals should be aware that avoiding numeric information to describe risks may not match patient preferences, and that patients interpret verbal risk terms in a highly variable way.

Seven decades of chemotherapy clinical trials: a pan-cancer social network analysis.

Clinical trials establish the standard of cancer care, yet the evolution and characteristics of the social dynamics between the people conducting this work remain understudied. We performed a social network analysis of authors publishing chemotherapy-based prospective trials from 1946 to 2018 to understand how social influences, including the role of gender, have influenced the growth and development of this network, which has expanded exponentially from fewer than 50 authors in 1946 to 29,197 in 2018. While 99.4% of authors were directly or indirectly connected by 2018, our results indicate a tendency to predominantly connect with others in the same or similar fields, as well as an increasing disparity in author impact and number of connections. Scale-free effects were evident, with small numbers of individuals having disproportionate impact. Women were under-represented and likelier to have lower impact, shorter productive periods (P < 0.001 for both comparisons), less centrality, and a greater proportion of co-authors in their same subspecialty. The past 30 years were characterized by a trend towards increased authorship by women, with new author parity anticipated in 2032. The network of cancer clinical trialists is best characterized as strategic or mixed-motive, with cooperative and competitive elements influencing its appearance. Network effects such as low centrality, which may limit access to high-profile individuals, likely contribute to the observed disparities.

Indication of Measures of Uncertainty for Statistical Significance in Abstracts of Published Oncology Trials: A Systematic Review and Meta-analysis.

IMPORTANCE: There is growing consensus that reliance on P values, particularly a cutoff level of .05 for statistical significance, is a factor in the challenges in scientific reproducibility. Despite this consensus, publications describing clinical trial results with P values near .05 anecdotally use declarative statements that do not express uncertainty. OBJECTIVES: To quantify uncertainty expression in abstracts describing the results of cancer randomized clinical trials (RCTs) with P values between .01 and .10 and examine whether trial features are associated with uncertainty expression. DATA SOURCES: A total of 5777 prospective trials indexed on HemOnc.org, as of September 15, 2019. STUDY SELECTION: Two-arm RCTs with a superiority end point with P values between .01 and .10. DATA EXTRACTION AND SYNTHESIS: Abstracts were evaluated based on an uncertainty expression algorithm. Ordinal logistic regression modeling with multiple imputation was performed to identify whether characteristics of study design, results, trial authors, and context P values were normalized by dividing by prespecified α value. MAIN OUTCOMES AND MEASURES: Uncertainty expression in abstracts as determined by the algorithm and its association with trial and publication characteristics. RESULTS: Of 5777 trials screened, 556 met analysis criteria. Of these, 222 trials (39.9%) did not express uncertainty, 161 trials (29.0%) expressed some uncertainty, and 173 trials (31.1%) expressed full uncertainty. In ordinal logistic regression with multiple imputation, trial features with statistically significant associations with uncertainty expression included later year of publication (odds ratio [OR], 1.70; 95% CI, 1.24-2.32; P < .001), normalized P value (OR, 1.36; 95% CI, 1.11-1.67; P = .003), noncooperative group studies (OR, 1.72; 95% CI, 1.12-2.63; P = .01), and reporting an end point other than overall survival (OR, 1.41; 95% CI, 1.01-1.96; P = .047). Funding source, number of authors, journal impact tier, author nationality, study of unapproved drugs, abstract word count, whether the marginal end point was a primary or coprimary end point, and effect size (in subgroup analysis) did not have statistically significant associations with uncertainty expression. CONCLUSIONS AND RELEVANCE: Published oncology articles with marginally significant results may often incompletely convey uncertainty. Although it appears that more uncertainty is expressed in recent abstracts, full uncertainty expression remains uncommon, and seemingly is less common when reporting overall survival, results with P values lower than α levels, and cooperative group studies.