N-Of-1 Trials: The Epitome of Personalized Medicine?

Observational studies are notoriously susceptible to bias, and parallel-group randomized trials are important to identify the best overall treatment for eligible patients. Yet, such trials can be expected to be a misleading indicator of the best treatment for some subgroups or individual patients. In selected circumstances, patients can be treated in n-of-1 trials to address the inherent heterogeneity of treatment response in clinical populations. Such trials help to accomplish the ultimate goal of all biomedical research, to optimize the care of individual patients

Intensive care for extreme prematurity--moving beyond gestational age.

BACKGROUND: Decisions regarding whether to administer intensive care to extremely premature infants are often based on gestational age alone. However, other factors also affect the prognosis for these patients. METHODS: We prospectively studied a cohort of 4446 infants born at 22 to 25 weeks\u27 gestation (determined on the basis of the best obstetrical estimate) in the Neonatal Research Network of the National Institute of Child Health and Human Development to relate risk factors assessable at or before birth to the likelihood of survival, survival without profound neurodevelopmental impairment, and survival without neurodevelopmental impairment at a corrected age of 18 to 22 months. RESULTS: Among study infants, 3702 (83%) received intensive care in the form of mechanical ventilation. Among the 4192 study infants (94%) for whom outcomes were determined at 18 to 22 months, 49% died, 61% died or had profound impairment, and 73% died or had impairment. In multivariable analyses of infants who received intensive care, exposure to antenatal corticosteroids, female sex, singleton birth, and higher birth weight (per each 100-g increment) were each associated with reductions in the risk of death and the risk of death or profound or any neurodevelopmental impairment; these reductions were similar to those associated with a 1-week increase in gestational age. At the same estimated likelihood of a favorable outcome, girls were less likely than boys to receive intensive care. The outcomes for infants who underwent ventilation were better predicted with the use of the above factors than with use of gestational age alone. CONCLUSIONS: The likelihood of a favorable outcome with intensive care can be better estimated by consideration of four factors in addition to gestational age: sex, exposure or nonexposure to antenatal corticosteroids, whether single or multiple birth, and birth weight. (ClinicalTrials.gov numbers, NCT00063063 [ClinicalTrials.gov] and NCT00009633 [ClinicalTrials.gov].)

Evaluation of Negative Binomial and Zero-Inflated Negative Binomial Models for the Analysis of Zero-Inflated Count Data: Application to the Telemedicine for Children With Medical Complexity Trial

BACKGROUND: Two characteristics of commonly used outcomes in medical research are zero inflation and non-negative integers; examples include the number of hospital admissions or emergency department visits, where the majority of patients will have zero counts. Zero-inflated regression models were devised to analyze this type of data. However, the performance of zero-inflated regression models or the properties of data best suited for these analyses have not been thoroughly investigated. METHODS: We conducted a simulation study to evaluate the performance of two generalized linear models, negative binomial and zero-inflated negative binomial, for analyzing zero-inflated count data. Simulation scenarios assumed a randomized controlled trial design and varied the true underlying distribution, sample size, and rate of zero inflation. We compared the models in terms of bias, mean squared error, and coverage. Additionally, we used logistic regression to determine which data properties are most important for predicting the best-fitting model. RESULTS: We first found that, regardless of the rate of zero inflation, there was little difference between the conventional negative binomial and its zero-inflated counterpart in terms of bias of the marginal treatment group coefficient. Second, even when the outcome was simulated from a zero-inflated distribution, a negative binomial model was favored above its ZI counterpart in terms of the Akaike Information Criterion. Third, the mean and skewness of the non-zero part of the data were stronger predictors of model preference than the percentage of zero counts. These results were not affected by the sample size, which ranged from 60 to 800. CONCLUSIONS: We recommend that the rate of zero inflation and overdispersion in the outcome should not be the sole and main justification for choosing zero-inflated regression models. Investigators should also consider other data characteristics when choosing a model for count data. In addition, if the performance of the NB and ZINB regression models is reasonably comparable even with ZI outcomes, we advocate the use of the NB regression model due to its clear and straightforward interpretation of the results

Advantages of Bayesian monitoring methods in deciding whether and when to stop a clinical trial: an example of a neonatal cooling trial.

BackgroundDecisions to stop randomized trials are often based on traditional P value thresholds and are often unconvincing to clinicians. To familiarize clinical investigators with the application and advantages of Bayesian monitoring methods, we illustrate the steps of Bayesian interim analysis using a recent major trial that was stopped based on frequentist analysis of safety and futility.MethodsWe conducted Bayesian reanalysis of a factorial trial in newborn infants with hypoxic-ischemic encephalopathy that was designed to investigate whether outcomes would be improved by deeper (32 °C) or longer cooling (120 h), as compared with those achieved by standard whole body cooling (33.5 °C for 72 h). Using prior trial data, we developed neutral and enthusiastic prior probabilities for the effect on predischarge mortality, defined stopping guidelines for a clinically meaningful effect, and derived posterior probabilities for predischarge mortality.ResultsBayesian relative risk estimates for predischarge mortality were closer to 1.0 than were frequentist estimates. Posterior probabilities suggested increased predischarge mortality (relative risk > 1.0) for the three intervention groups; two crossed the Bayesian futility threshold.ConclusionsBayesian analysis incorporating previous trial results and different pre-existing opinions can help interpret accruing data and facilitate informed stopping decisions that are likely to be meaningful and convincing to clinicians, meta-analysts, and guideline developers.Trial registrationClinicalTrials.gov NCT01192776 . Registered on 31 August 2010

Special Considerations in Randomized Trials Investigating Neonatal Surgical Treatments

Randomized controlled trials (RCTs) are challenging, but are the studies most likely to change practice and benefit patients. RCTs investigating neonatal surgical therapies are rare. The Necrotizing Enterocolitis Surgery Trial (NEST) was the first surgical RCT conducted by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Neonatal Research Network (NRN), and multiple lessons were learned. NEST was conducted over a 7.25-year enrollment period and the primary outcome was death or neurodevelopmental impairment (NDI) at 18-22 months corrected age. Surgical investigators designing clinical trials involving neonatal surgical treatments have many considerations to include, including how to study eligible but non-randomized patients, heterogeneity of treatment effect, use of frequentist and Bayesian analyses, assessment of generalizability, and anticipating criticisms during peer review. Surgeons are encouraged to embrace these challenges and seek innovative methods to acquire evidence that will be used to improve patient outcomes

Outcome Prediction in Newborn Infants: Past, Present, and Future

The perinatal and neonatal periods are the periods of considerable organ development and maturation. Perinatal and neonatal illnesses can result in mortality and morbidities that burden families and the healthcare system. Outcome prediction is essential for informing perinatal and intensive care management, prognosis, and post-discharge interventions. The Eunice Kennedy Shriver National Institute of Child Health and Human Development Neonatal Research Network (NRN) research databases include hospital and neurodevelopment follow-up outcomes of infants with various underlying diseases and conditions receiving intensive care, providing a unique opportunity to assess outcome risk prediction. The NRN has developed outcome risk prediction tools for use in infants with various diseases and conditions that allow data-driven, transparent discussions to inform family-focused communications and clinical management. This review presents the published neonatal outcome risk prediction research from the NRN, their present clinical utility, and possible future directions for advanced individualized risk prediction

N-of-1 Trials vs. Usual Care in Children With Hypertension: A Pilot Randomized Clinical Trial

BACKGROUND: Blood pressure (BP) is often inadequately controlled in children treated for hypertension, and personalized (n-of-1) trials show promise for tailoring treatment choices. We assessed whether patients whose treatment choices are informed by an n-of-1 trial have improved BP control compared to usual care. METHODS: A randomized clinical trial was conducted in a pediatric hypertension clinic in Houston from April 2018 to September 2020. Hypertensive adolescents and young adults 10-22 years old were randomized 1:1 to a strategy of n-of-1 trial using ambulatory BP monitoring to inform treatment choice or usual care, with treatment selected by physician preference. The primary outcome was the proportion of patients with ambulatory BP control at 6 months in a Bayesian analysis. RESULTS: Among 49 participants (23 randomized to n-of-1 trials and 26 to usual care), mean age was 15.6 years. Using skeptical priors, we found a 69% probability that n-of-1 trials increased BP control at 6 months (Bayesian odds ratio (OR) 1.24 (95% credible interval (CrI) 0.51, 2.97), and 74% probability using neutral informed priors (OR 1.45 (95% CrI 0.48, 4.53)). Systolic BP was reduced in both groups, with a 93% probability of greater reduction in the n-of-1 trial group (mean difference between groups = -3.6 mm Hg (95% CrI -8.3, 1.28). There was no significant difference in side effect experience or caregiver satisfaction. CONCLUSIONS: Among hypertensive adolescents and young adults, n-of-1 trials with ambulatory BP monitoring likely increased the probability of BP control. A large trial is needed to assess their use in clinical practice. CLINICALTRIALS.GOV: NCT03461003. CLINICAL TRIAL REGISTRY: ClinicalTrials.gov; NCT03461003

Operator-Schmidt decompositions and the Fourier transform, with applications to the operator-Schmidt numbers of unitaries

The operator-Schmidt decomposition is useful in quantum information theory for quantifying the nonlocality of bipartite unitary operations. We construct a family of unitary operators on C^n tensor C^n whose operator-Schmidt decompositions are computed using the discrete Fourier transform. As a corollary, we produce unitaries on C^3 tensor C^3 with operator-Schmidt number S for every S in {1,...,9}. This corollary was unexpected, since it contradicted reasonable conjectures of Nielsen et al [Phys. Rev. A 67 (2003) 052301] based on intuition from a striking result in the two-qubit case. By the results of Dur, Vidal, and Cirac [Phys. Rev. Lett. 89 (2002) 057901 quant-ph/0112124], who also considered the two-qubit case, our result implies that there are nine equivalence classes of unitaries on C^3 tensor C^3 which are probabilistically interconvertible by (stochastic) local operations and classical communication. As another corollary, a prescription is produced for constructing maximally-entangled operators from biunimodular functions. Reversing tact, we state a generalized operator-Schmidt decomposition of the quantum Fourier transform considered as an operator C^M_1 tensor C^M_2 --> C^N_1 tensor C^N_2, with M_1 x M_2 = N_1 x N_2. This decomposition shows (by Nielsen's bound) that the communication cost of the QFT remains maximal when a net transfer of qudits is permitted. In an appendix, a canonical procedure is given for removing basis-dependence for results and proofs depending on the "magic basis" introduced in [S. Hill and W. Wootters, "Entanglement of a pair of quantum bits," Phys Rev. Lett 78 (1997) 5022-5025, quant-ph/9703041 (and quant-ph/9709029)].Comment: More formal version of my talk at the Simons Conference on Quantum and Reversible Computation at Stony Brook May 31, 2003. The talk slides and audio are available at http://www.physics.sunysb.edu/itp/conf/simons-qcomputation.html. Fixed typos and minor cosmetic

Randomized Controlled Trial of Enteral Vitamin D Supplementation (ViDES) in Infants \u3c28 Weeks Gestational Age or \u3c1000 G Birth Weight: Study Protocol

BACKGROUND: Vitamin D is necessary to develop healthy lungs and other organs early in life. Most infants born before 28 weeks\u27 gestation have low vitamin D levels at birth and a limited intake during the first month. Enteral vitamin D supplementation is inexpensive and widely used. The appropriate supplementation regimen for extremely preterm infants is controversial, and the effect of different regimens on their blood levels and outcomes is unclear. METHODS: Randomized, blinded comparative effectiveness trial to compare two vitamin D supplementation regimens for inborn infants(400 IU/day with established feedings) or increased supplementation (800 IU/day with any feedings) during the first 28 days after birth. We hypothesize that the higher and early vitamin D dose (800 IU/day with early feeding) compared to placebo plus routine dose (400 IU/day with established feeding) will substantially increase total 25-hydroxyvitamin D3 levels measured as state-of-art at 1 month, reduce respiratory support at 36 weeks\u27 postmenstrual age (on an ordinal scale predictive of later adverse outcomes), and improve or at least not worsen other important secondary outcomes. The infants in the study will follow up at 22-26 months\u27 corrected age (~2 years) with blinded certified examiners to evaluate neurodevelopmental outcomes. The sample size of a minimum of 180 infants provides \u3e90% power to detect a \u3e95% posterior probability of a 33% increase in serum 25-hydroxy vitamin D3 and \u3e80% power to detect a \u3e80% posterior probability of a relative risk decrease of 20% of reducing respiratory support by intention-to-treat Bayesian analyses using a neutral prior probability. DISCUSSION: Our study will help clarify the uncertain relationship of vitamin D supplementation and its associated serum metabolites to clinical outcomes of extremely preterm infants. Confirmation of our hypotheses would prompt reconsideration of the supplementation regimens used in extremely preterm infants and justify a large multicenter study to verify the generalizability of the results

Hospital-Level NICU Capacity, Utilization, and 30-Day Outcomes in Texas

IMPORTANCE: Risk-adjusted neonatal intensive care unit (NICU) utilization and outcomes vary markedly across regions and hospitals. The causes of this variation are poorly understood. OBJECTIVE: To assess the association of hospital-level NICU bed capacity with utilization and outcomes in newborn cohorts with differing levels of health risk. DESIGN, SETTING, AND PARTICIPANTS: This population-based retrospective cohort study included all Medicaid-insured live births in Texas from 2010 to 2014 using linked vital records and maternal and newborn claims data. Participants were Medicaid-insured singleton live births (LBs) with birth weights of at least 400 g and gestational ages between 22 and 44 weeks. Newborns were grouped into 3 cohorts: very low birth weight (VLBW; \u3c1500 \u3eg), late preterm (LPT; 34-36 weeks\u27 gestation), and nonpreterm newborns (NPT; ≥37 weeks\u27 gestation). Data analysis was conducted from January 2022 to October 2023. EXPOSURE: Hospital NICU capacity measured as reported NICU beds/100 LBs, adjusted (ie, allocated) for transfers. MAIN OUTCOMES AND MEASURES: NICU admissions and special care days; inpatient mortality and 30-day postdischarge adverse events (ie, mortality, emergency department visit, admission, observation stay). RESULTS: The overall cohort of 874 280 single LBs included 9938 VLBW (5054 [50.9%] female; mean [SD] birth weight, 1028.9 [289.6] g; mean [SD] gestational age, 27.6 [2.6] wk), 63 160 LPT (33 684 [53.3%] female; mean [SD] birth weight, 2664.0 [409.4] g; mean [SD] gestational age, 35.4 [0.8] wk), and 801 182 NPT (407 977 [50.9%] female; mean [SD] birth weight, 3318.7 [383.4] g; mean [SD] gestational age, 38.9 [1.0] wk) LBs. Median (IQR) NICU capacity was 0.84 (0.57-1.30) allocated beds/100 LB/year. For VLBW newborns, NICU capacity was not associated with the risk of NICU admission or number of special care days. For LPT newborns, birth in hospitals with the highest compared with the lowest category of capacity was associated with a 17% higher risk of NICU admission (adjusted risk ratio [aRR], 1.17; 95% CI, 1.01-1.33). For NPT newborns, risk of NICU admission was 55% higher (aRR, 1.55; 95% CI, 1.22-1.97) in the highest- vs the lowest-capacity hospitals. The number of special care days for LPT and NPT newborns was 21% (aRR, 1.21; 95% CI,1.08-1.36) and 37% (aRR, 1.37; 95% CI, 1.08-1.74) higher in the highest vs lowest capacity hospitals, respectively. Among LPT and NPT newborns, NICU capacity was associated with higher inpatient mortality and 30-day postdischarge adverse events. CONCLUSIONS AND RELEVANCE: In this cohort study of Medicaid-insured newborns in Texas, greater hospital NICU bed supply was associated with increased NICU utilization in newborns born LPT and NPT. Higher capacity was not associated with lower risk of adverse events. These findings raise important questions about how the NICU is used for newborns with lower risk