Modeling basal body temperature data using horseshoe process regression

Biomedical data often exhibit jumps or abrupt changes. For example, women's basal body temperature may jump at ovulation, menstruation, implantation, and miscarriage. These sudden changes make these data challenging to model: many methods will oversmooth the sharp changes or overfit in response to measurement error. We develop horseshoe process regression (HPR) to address this problem. We define a horseshoe process as a stochastic process in which each increment is horseshoe-distributed. We use the horseshoe process as a nonparametric Bayesian prior for modeling a potentially nonlinear association between an outcome and its continuous predictor, which we implement via Stan and in the R package HPR. We provide guidance and extensions to advance HPR's use in applied practice: we introduce a Bayesian imputation scheme to allow for interpolation at unobserved values of the predictor within the HPR; include additional covariates via a partial linear model framework; and allow for monotonicity constraints. We find that HPR performs well when fitting functions that have sharp changes. We apply HPR to model women's basal body temperatures over the course of the menstrual cycle.

Shrinkage priors for isotonic probability vectors and binary data modeling, with applications to dose-response modeling

Motivated by the need to model dose-response or dose-toxicity curves in clinical trials, we develop a new horseshoe-based prior for Bayesian isotonic regression modeling a binary outcome against an ordered categorical predictor, where the probability of the outcome is assumed to be monotonically non-decreasing with the predictor. The set of differences between outcome probabilities in consecutive categories of the predictor is equipped with a multivariate prior having support over simplex. The Dirichlet distribution, which can be derived from a normalized sum of independent gamma-distributed random variables, is a natural choice of prior, but using mathematical and simulation-based arguments, we show that the resulting posterior is prone to underflow and other numerical instabilities, even under simple data configurations. We propose an alternative prior based on horseshoe-type shrinkage that is numerically more stable. We show that this horseshoe-based prior is not subject to the numerical instability seen in the Dirichlet/gamma-based prior and that the horseshoe-based posterior can estimate the underlying true curve more efficiently than the Dirichlet-based one. We demonstrate the use of this prior in a model predicting the occurrence of radiation-induced lung toxicity in lung cancer patients as a function of dose delivered to normal lung tissue. Our methodology is implemented in the R package isotonicBayes and therefore suitable for use in the design of dose-finding studies or other dose-response modeling contexts.

Extracorporeal Life Support Organization Registry International Report 2022: 100,000 Survivors

The Extracorporeal Life Support Organization (ELSO) maintains the world's largest extracorporeal membrane oxygenation (ECMO) registry by volume, center participation, and international scope. This 2022 ELSO Registry Report describes the program characteristics of ECMO centers, processes of ECMO care, and reported outcomes. Neonates (0-28 days), children (29 days-17 years), and adults (≥18 years) supported with ECMO from 2009 through 2022 and reported to the ELSO Registry were included. This report describes adjunctive therapies, support modes, treatments, complications, and survival outcomes. Data are presented descriptively as counts and percent or median and interquartile range (IQR) by year, group, or level. Missing values were excluded before calculating descriptive statistics. Complications are reported per 1,000 ECMO hours. From 2009 to 2022, 154,568 ECMO runs were entered into the ELSO Registry. Seven hundred and eighty centers submitted data during this time (557 in 2022). Since 2009, the median annual number of adult ECMO runs per center per year increased from 4 to 15, whereas for pediatric and neonatal runs, the rate decreased from 12 to 7. Over 50% of patients were transferred to the reporting ECMO center; 20% of these patients were transported with ECMO. The use of prone positioning before respiratory ECMO increased from 15% (2019) to 44% (2021) for adults during the coronavirus disease-2019 (COVID-19) pandemic. Survival to hospital discharge was greatest at 68.5% for neonatal respiratory support and lowest at 29.5% for ECPR delivered to adults. By 2022, the Registry had enrolled its 200,000th ECMO patient and 100,000th patient discharged alive. Since its inception, the ELSO Registry has helped centers measure and compare outcomes across its member centers and strategies of care. Continued growth and development of the Registry will aim to bolster its utility to patients and centers.

Optimizing the doses of cancer drugs after usual dose finding

Since the middle of the 20th century, oncology's dose-finding paradigm has been oriented toward identifying a drug's maximum tolerated dose, which is then carried forward into phase 2 and 3 trials and clinical practice. For most modern precision medicines, however, maximum tolerated dose is far greater than the minimum dose needed to achieve maximal benefit, leading to unnecessary side effects. Regulatory change may decrease maximum tolerated dose's predominance by enforcing dose optimization of new drugs. Dozens of already approved cancer drugs require re-evaluation, however, introducing a new methodologic and ethical challenge in cancer clinical trials. In this article, we assess the history and current landscape of cancer drug dose finding. We provide a set of strategic priorities for postapproval dose optimization trials of the future. We discuss ethical considerations for postapproval dose optimization trial design and review three major design strategies for these unique trials that would both adhere to ethical standards and benefit patients and funders. We close with a discussion of financial and reporting considerations in the realm of dose optimization. Taken together, we provide a comprehensive, bird's eye view of the postapproval dose optimization trial landscape and offer our thoughts on the next steps required of methodologies and regulatory and funding regimes.

Targeted randomization dose optimization trials enable fractional dosing of scarce drugs

Administering drug at a dose lower than that used in pivotal clinical trials, known as fractional dosing, can stretch scarce resources. Implementing fractional dosing with confidence requires understanding a drug's dose-response relationship. Clinical trials aimed at describing dose-response in scarce, efficacious drugs risk underdosing, leading dose-finding trials to not be pursued despite their obvious potential benefit. We developed a new set of response-adaptive randomized dose-finding trials and demonstrate, in a series of simulated trials across diverse dose-response curves, these designs' efficiency in identifying the minimum dose that achieves satisfactory efficacy. Compared to conventional designs, these trials have higher probabilities of identifying lower doses while reducing the risks of both population- and subject-level underdosing. We strongly recommend that, upon demonstration of a drug's efficacy, pandemic drug development swiftly proceeds with response-adaptive dose-finding trials. This unified strategy ensures that scarce effective drugs produce maximum social benefits.

Evaluating feasibility of a novel mobile emergency medical dispatch tool for lay first responder prehospital response coordination in Sierra Leone: A simulation-based study

INTRODUCTION

The global injury burden, driven by road traffic injuries, disproportionately affects low- and middle-income countries, which lack robust emergency medical services (EMS) to address injury. The WHO recommends training lay first responders (LFRs) as the first step toward formal EMS development. Emergency medical dispatch (EMD) systems are the recognized next step but whether small groups of LFRs equipped with mobile dispatch infrastructure can efficiently respond to geographically-dispersed emergencies in a timely fashion and the quality of prehospital care provided is unknown.

MATERIALS AND METHODS

We piloted an EMD system utilizing a mobile phone application in Sierra Leone. Ten LFRs were randomly selected from a pool of 61 highly-active LFRs trained in 2019 and recruited to participate in an emergency simulation-based study. Ten simulation scenarios were created matching proportions of injury conditions across 1,850 previous incidents (June-December 2019). Fifty total simulations were launched in randomized order over 3 months, randomized along 10 km of highway in Makeni. Replicating real-world conditions, highly-active LFR participants were blinded to randomized dispatch timing/scenario to assess response time and skill performance under direct observation with a checklist using standardized patient actors. We used novel cost data tracked during EMD pilot implementation to inform the calculation of a new cost-effectiveness ratio ($USD cost per disability-adjusted life year averted (DALY)) for LFR programs equipped with dispatch, following WHOCHOICE guidelines, which state cost-effectiveness ratios less than gross domestic product (GDP) per capita are considered "very cost-effective."

RESULTS

Median total response interval (notification to arrival) was 5 min 39 s (IQR:0:03:51, 0:09:18). LFRs initially trained with a 5-hour curriculum and refresher training provide high-quality prehospital care during simulated emergencies. Median first aid skill checklist completion was 89% (IQR: 78%, 90%). Cost-effectiveness equals $179.02USD per DALY averted per 100,000 people, less than Sierra Leonean GDP per capita ($484.52USD).

CONCLUSION

LFRs equipped with mobile dispatch demonstrate appropriate response times and effective basic initial management of simulated emergencies. Training smaller cohorts of highly-active LFRs equipped with mobile dispatch appears highly cost-effective and may be a feasible model to facilitate efficient dispatch to expand emergency coverage while conserving valuable training resources in resource-limited settings.

A real-world experience: Outcomes among relapsed/refractory diffuse large B cell lymphoma patients with CD20 loss

e19570

Background: Despite novel therapies for relapsed/refractory (R/R) DLBCL, outcomes among this cohort remain poor. A prior study indicated that patients who lost CD20 expression after treatment have earlier disease progression, but whether this translates to inferior outcomes remains unknown. We hypothesized that R/R DLBCL patients who lost CD20 expression upon disease relapse would have worse survival and response rates compared to those who retained expression. Methods: We performed a retrospective cohort study of R/R DLBCL patients seen at the University of Michigan between 2007-2021. Inclusion criteria were patients ≥ 18 years old, diagnosis of CD20 positive (+) DLBCL (de novo or transformed), relapsed/refractory disease, and CD20 status available at relapse on flow cytometry/immunohistochemistry. Overall survival (OS) was defined as time from first relapse to death and relapse-free survival (RFS) was time from first relapse to death or next treatment; both of which were estimated with Kaplan Meier analysis. Overall response rate (ORR) was complete response or partial response after first salvage therapy. Descriptive statistics with univariate and multivariate analyses were also performed. Results: 98 patients were included (65% male) with median age at diagnosis of 62 years. Majority of patients had stage III/IV disease at diagnosis (85%), 45% with GCB subtype and 7% with high-grade lymphoma. At diagnosis, all patients had CD20+ disease. Median time from diagnosis to first relapse was 7 months and median time from completion of induction treatment to first relapse was 2.4 months. Among the 98 patients, 84 were CD20+ at first relapse, 12 were CD20 negative and the remaining 2 patients were indeterminate and excluded from survival analyses. The estimated OS in the CD20+ group was 17.9 months (95% CI 14.0, 41.8) compared to 10.6 months in the CD20 negative group (95% CI 6.9, Not Reached). Although median OS in the CD20+ group was longer, a two-sample log-rank test failed to identify a significant difference in OS between the two groups (p = 0.085). The estimated RFS in the CD20+ group was 3.5 months (95% CI 3.3, 3.9) compared to 4.4 months in the CD20 negative group (95% CI 2.6, Not Reached, p = 0.739). ORR among CD20+ and CD20 negative patients was 64% and 50%, respectively. Of patients who became CD20 negative at relapse, 100% received anti-CD20 directed therapy thereafter, as part of salvage or with conditioning prior to transplant. Conclusions: Patients with DLBCL who relapse and maintain CD20 positivity seem to have a trend towards longer OS, though this was not statistically significant in our analysis. Our study was limited given the retrospective data collection and small sample size which may have limited our ability to detect a statistical significance in outcomes. In the future, we will plan to expand our study to involve other academic institutions and reassess outcomes among these cohorts.

Utility based approach in individualized optimal dose selection using machine learning methods

The goal in personalized medicine is to individualize treatment using patient characteristics and improve health outcomes. Selection of optimal dose must balance the effect of dose on both treatment efficacy and toxicity outcomes. We consider a setting with one binary efficacy and one binary toxicity outcome. The goal is to find the optimal dose for each patient using clinical features and biomarkers from available dataset. We propose to use flexible machine learning methods such as random forest and Gaussian process models to build models for efficacy and toxicity depending on dose and biomarkers. A copula is used to model the joint distribution of the two outcomes and the estimates are constrained to have non‐decreasing dose‐efficacy and dose‐toxicity relationships. Numerical utilities are elicited from clinicians for each potential bivariate outcome. For each patient, the optimal dose is chosen to maximize the posterior mean of the utility function. We also propose alternative approaches to optimal dose selection by adding additional toxicity based constraints and an approach taking into account the uncertainty in the estimation of the utility function. The proposed methods are evaluated in a simulation study to compare expected utility outcomes under various estimated optimal dose rules. Gaussian process models tended to have better performance than random forest. Enforcing monotonicity during modeling provided small benefits. Whether and how, correlation between efficacy and toxicity, was modeled, had little effect on performance. The proposed methods are illustrated with a study of patients with liver cancer treated with stereotactic body radiation therapy.

Extracorporeal membrane oxygenation for COVID-19: evolving outcomes from the international Extracorporeal Life Support Organization Registry

BACKGROUND

Over the course of the COVID-19 pandemic, the care of patients with COVID-19 has changed and the use of extracorporeal membrane oxygenation (ECMO) has increased. We aimed to examine patient selection, treatments, outcomes, and ECMO centre characteristics over the course of the pandemic to date.

METHODS

We retrospectively analysed the Extracorporeal Life Support Organization Registry and COVID-19 Addendum to compare three groups of ECMO-supported patients with COVID-19 (aged ≥16 years). At early-adopting centres-ie, those using ECMO support for COVID-19 throughout 2020-we compared patients who started ECMO on or before May 1, 2020 (group A1), and between May 2 and Dec 31, 2020 (group A2). Late-adopting centres were those that provided ECMO for COVID-19 only after May 1, 2020 (group B). The primary outcome was in-hospital mortality in a time-to-event analysis assessed 90 days after ECMO initiation. A Cox proportional hazards model was fit to compare the patient and centre-level adjusted relative risk of mortality among the groups.

FINDINGS

In 2020, 4812 patients with COVID-19 received ECMO across 349 centres within 41 countries. For early-adopting centres, the cumulative incidence of in-hospital mortality 90 days after ECMO initiation was 36·9% (95% CI 34·1-39·7) in patients who started ECMO on or before May 1 (group A1) versus 51·9% (50·0-53·8) after May 1 (group A2); at late-adopting centres (group B), it was 58·9% (55·4-62·3). Relative to patients in group A2, group A1 patients had a lower adjusted relative risk of in-hospital mortality 90 days after ECMO (hazard ratio 0·82 [0·70-0·96]), whereas group B patients had a higher adjusted relative risk (1·42 [1·17-1·73]).

INTERPRETATION

Mortality after ECMO for patients with COVID-19 worsened during 2020. These findings inform the role of ECMO in COVID-19 for patients, clinicians, and policy makers.

FUNDING

None.

ASSESSING SELECTION BIAS IN REGRESSION COEFFICIENTS ESTIMATED FROM NONPROBABILITY SAMPLES WITH APPLICATIONS TO GENETICS AND DEMOGRAPHIC SURVEYS

Selection bias is a serious potential problem for inference about relationships of scientific interest based on samples without well-defined probability sampling mechanisms. Motivated by the potential for selection bias in: (a) estimated relationships of polygenic scores (PGSs) with phenotypes in genetic studies of volunteers and (b) estimated differences in subgroup means in surveys of smartphone users, we derive novel measures of selection bias for estimates of the coefficients in linear and probit regression models fitted to nonprobability samples, when aggregate-level auxiliary data are available for the selected sample and the target population. The measures arise from normal pattern-mixture models that allow analysts to examine the sensitivity of their inferences to assumptions about nonignorable selection in these samples. We examine the effectiveness of the proposed measures in a simulation study and then use them to quantify the selection bias in: (a) estimated PGS-phenotype relationships in a large study of volunteers recruited via Facebook and (b) estimated subgroup differences in mean past-year employment duration in a nonprobability sample of low-educated smartphone users. We evaluate the performance of the measures in these applications using benchmark estimates from large probability samples.

A simulation study of diagnostics for selection bias

A non-probability sampling mechanism arising from non-response or non-selection is likely to bias estimates of parameters with respect to a target population of interest. This bias poses a unique challenge when selection is 'non-ignorable', i.e. dependent upon the unobserved outcome of interest, since it is then undetectable and thus cannot be ameliorated. We extend a simulation study by Nishimura et al. [International Statistical Review, 84, 43-62 (2016)], adding two recently published statistics: the so-called 'standardized measure of unadjusted bias (SMUB)' and 'standardized measure of adjusted bias (SMAB)', which explicitly quantify the extent of bias (in the case of SMUB) or non-ignorable bias (in the case of SMAB) under the assumption that a specified amount of non-ignorable selection exists. Our findings suggest that this new sensitivity diagnostic is more correlated with, and more predictive of, the true, unknown extent of selection bias than other diagnostics, even when the underlying assumed level of non-ignorability is incorrect.

Evaluating a Novel Prehospital Emergency Trauma Care Assessment Tool (PETCAT) for Low- and Middle-Income Countries in Sierra Leone

BACKGROUND

WHO recommends training lay first responders (LFRs) as the first step toward formal emergency medical services development, yet no tool exists to evaluate LFR programs.

METHODS

We developed Prehospital Emergency Trauma Care Assessment Tool (PETCAT), a seven-question survey administered to first-line hospital-based healthcare providers, to independently assess LFR prehospital intervention frequency and quality. PETCAT surveys were administered one month pre-LFR program launch (June 2019) in Makeni, Sierra Leone and again 14 months post-launch (August 2020). Using a difference-in-differences approach, PETCAT was also administered in a control city (Kenema) with no LFR training intervention during the study period at the same intervals to control for secular trends. PETCAT measured change in both the experimental and control locations. Cronbach's alpha, point bi-serial correlation, and inter-rater reliability using Cohen's Kappa assessed PETCAT reliability.

RESULTS

PETCAT administration to 90 first-line, hospital-based healthcare providers found baseline prehospital intervention were rare in Makeni and Kenema prior to LFR program launch (1.2/10 vs. 1.8/10). Fourteen months post-LFR program implementation, PETCAT demonstrated prehospital interventions increased in Makeni with LFRs (5.2/10, p < 0.0001) and not in Kenema (1.2/10) by an adjusted difference of + 4.6 points/10 (p < 0.0001) ("never/rarely" to "half the time"), indicating negligible change due to secular trends. PETCAT demonstrated high reliability (Cronbach's α = 0.93, Cohen's K = 0.62).

CONCLUSIONS

PETCAT measures changes in rates of prehospital care delivery by LFRs in a resource-limited African setting and may serve as a robust tool for independent EMS quality assessment.

Investigating the SPECT Dose-Function Metrics Associated With Radiation-Induced Lung Toxicity Risk in Patients With Non-small Cell Lung Cancer Undergoing Radiation Therapy

Purpose

Dose to normal lung has commonly been linked with radiation-induced lung toxicity (RILT) risk, but incorporating functional lung metrics in treatment planning may help further optimize dose delivery and reduce RILT incidence. The purpose of this study was to investigate the impact of the dose delivered to functional lung regions by analyzing perfusion (Q), ventilation (V), and combined V/Q single-photon-emission computed tomography (SPECT) dose-function metrics with regard to RILT risk in patients with non-small cell lung cancer (NSCLC) patients who received radiation therapy (RT).

Methods and Materials

SPECT images acquired from 88 patients with locally advanced NSCLC before undergoing conventionally fractionated RT were retrospectively analyzed. Dose was converted to the nominal dose equivalent per 2 Gy fraction, and SPECT intensities were normalized. Regional lung segments were defined, and the average dose delivered to each lung region was quantified. Three functional categorizations were defined to represent low-, normal-, and high-functioning lungs. The percent of functional lung category receiving ≥20 Gy and mean functional intensity receiving ≥20 Gy (iV₂₀) were calculated. RILT was defined as grade 2+ radiation pneumonitis and/or clinical radiation fibrosis. A logistic regression was used to evaluate the association between dose-function metrics and risk of RILT.

Results

By analyzing V/Q normalized intensities and functional distributions across the population, a wide range in functional capability (especially in the ipsilateral lung) was observed in patients with NSCLC before RT. Through multivariable regression models, global lung average dose to the lower lung was found to be significantly associated with RILT, and Q and V iV₂₀ were correlated with RILT when using ipsilateral lung metrics. Through a receiver operating characteristic analysis, combined V/Q low-function receiving ≥20 Gy (low-functioning V/Q₂₀) in the ipsilateral lung was found to be the best predictor (area under the curce: 0.79) of RILT risk.

Conclusions

Irradiation of the inferior lung appears to be a locational sensitivity for RILT risk. The multivariable correlation between ipsilateral lung iV₂₀ and RILT, as well as the association of low-functioning V/Q₂₀ and RILT, suggest that irradiating low-functioning regions in the lung may lead to higher toxicity rates.

A modular framework for early-phase seamless oncology trials

BACKGROUND

As our understanding of the etiology and mechanisms of cancer becomes more sophisticated and the number of therapeutic options increases, phase I oncology trials today have multiple primary objectives. Many such designs are now "seamless," meaning that the trial estimates both the maximum tolerated dose and the efficacy at this dose level. Sponsors often proceed with further study only with this additional efficacy evidence. However, with this increasing complexity in trial design, it becomes challenging to articulate fundamental operating characteristics of these trials, such as (1) what is the probability that the design will identify an acceptable, that is., safe and efficacious, dose level? or (2) how many patients will be assigned to an acceptable dose level on average?

METHODS

In this manuscript, we propose a new modular framework for designing and evaluating seamless oncology trials. Each module is comprised of either a dose assignment step or a dose-response evaluation, and multiple such modules can be implemented sequentially. We develop modules from existing phase I/II designs as well as a novel module for evaluating dose-response using a Bayesian isotonic regression scheme.

RESULTS

We also demonstrate a freely available R package called seamlesssim to numerically estimate, by means of simulation, the operating characteristics of these modular trials.

CONCLUSIONS

Together, this design framework and its accompanying simulator allow the clinical trialist to compare multiple different candidate designs, more rigorously assess performance, better justify sample sizes, and ultimately select a higher quality design.

Measures of the Degree of Departure from Ignorable Sample Selection

With the current focus of survey researchers on "big data" that are not selected by probability sampling, measures of the degree of potential sampling bias arising from this nonrandom selection are sorely needed. Existing indices of this degree of departure from probability sampling, like the R-indicator, are based on functions of the propensity of inclusion in the sample, estimated by modeling the inclusion probability as a function of auxiliary variables. These methods are agnostic about the relationship between the inclusion probability and survey outcomes, which is a crucial feature of the problem. We propose a simple index of degree of departure from ignorable sample selection that corrects this deficiency, which we call the standardized measure of unadjusted bias (SMUB). The index is based on normal pattern-mixture models for nonresponse applied to this sample selection problem and is grounded in the model-based framework of nonignorable selection first proposed in the context of nonresponse by Don Rubin in 1976. The index depends on an inestimable parameter that measures the deviation from selection at random, which ranges between the values zero and one. We propose the use of a central value of this parameter, 0.5, for computing a point index, and computing the values of SMUB at zero and one to provide a range of the index in a sensitivity analysis. We also provide a fully Bayesian approach for computing credible intervals for the SMUB, reflecting uncertainty in the values of all of the input parameters. The proposed methods have been implemented in R and are illustrated using real data from the National Survey of Family Growth.

Extracorporeal membrane oxygenation support in COVID-19: an international cohort study of the Extracorporeal Life Support Organization registry

BACKGROUND

Multiple major health organisations recommend the use of extracorporeal membrane oxygenation (ECMO) support for COVID-19-related acute hypoxaemic respiratory failure. However, initial reports of ECMO use in patients with COVID-19 described very high mortality and there have been no large, international cohort studies of ECMO for COVID-19 reported to date.

METHODS

We used data from the Extracorporeal Life Support Organization (ELSO) Registry to characterise the epidemiology, hospital course, and outcomes of patients aged 16 years or older with confirmed COVID-19 who had ECMO support initiated between Jan 16 and May 1, 2020, at 213 hospitals in 36 countries. The primary outcome was in-hospital death in a time-to-event analysis assessed at 90 days after ECMO initiation. We applied a multivariable Cox model to examine whether patient and hospital factors were associated with in-hospital mortality.

FINDINGS

Data for 1035 patients with COVID-19 who received ECMO support were included in this study. Of these, 67 (6%) remained hospitalised, 311 (30%) were discharged home or to an acute rehabilitation centre, 101 (10%) were discharged to a long-term acute care centre or unspecified location, 176 (17%) were discharged to another hospital, and 380 (37%) died. The estimated cumulative incidence of in-hospital mortality 90 days after the initiation of ECMO was 37·4% (95% CI 34·4-40·4). Mortality was 39% (380 of 968) in patients with a final disposition of death or hospital discharge. The use of ECMO for circulatory support was independently associated with higher in-hospital mortality (hazard ratio 1·89, 95% CI 1·20-2·97). In the subset of patients with COVID-19 receiving respiratory (venovenous) ECMO and characterised as having acute respiratory distress syndrome, the estimated cumulative incidence of in-hospital mortality 90 days after the initiation of ECMO was 38·0% (95% CI 34·6-41·5).

INTERPRETATION

In patients with COVID-19 who received ECMO, both estimated mortality 90 days after ECMO and mortality in those with a final disposition of death or discharge were less than 40%. These data from 213 hospitals worldwide provide a generalisable estimate of ECMO mortality in the setting of COVID-19.

FUNDING

None.

Inferring a consensus problem list using penalized multistage models for ordered data

A patient's medical problem list describes his or her current health status and aids in the coordination and transfer of care between providers. Because a problem list is generated once and then subsequently modified or updated, what is not usually observable is the provider-effect. That is, to what extent does a patient's problem in the electronic medical record actually reflect a consensus communication of that patient's current health status? To that end, we report on and analyze a unique interview-based design in which multiple medical providers independently generate problem lists for each of three patient case abstracts of varying clinical difficulty. Due to the uniqueness of both our data and the scientific objectives of our analysis, we apply and extend so-called multistage models for ordered lists and equip the models with variable selection penalties to induce sparsity. Each problem has a corresponding non-negative parameter estimate, interpreted as a relative log-odds ratio, with larger values suggesting greater importance and zero values suggesting unimportant problems. We use these fitted penalized models to quantify and report the extent of consensus. We conduct a simulation study to evaluate the performance of our methodology and then analyze the motivating problem list data. For the three case abstracts, the proportions of problems with model-estimated non-zero log-odds ratios were 10/28, 16/47, and 13/30. Physicians exhibited consensus on the highest ranked problems in the first and last case abstracts but agreement quickly deteriorated; in contrast, physicians broadly disagreed on the relevant problems for the middle - and most difficult - case abstract.

Serial Molecular Profiling of Low-grade Prostate Cancer to Assess Tumor Upgrading: A Longitudinal Cohort Study

BACKGROUND

The potential for low-grade (grade group 1 [GG1]) prostate cancer (PCa) to progress to high-grade disease remains unclear.

OBJECTIVE

To interrogate the molecular and biological features of low-grade PCa serially over time.

DESIGN, SETTING, AND PARTICIPANTS

Nested longitudinal cohort study in an academic active surveillance (AS) program. Men were on AS for GG1 PCa from 2012 to 2017.

INTERVENTION

Electronic tracking and resampling of PCa using magnetic resonance imaging/ultrasound fusion biopsy.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

ERG immunohistochemistry (IHC) and targeted DNA/RNA next-generation sequencing were performed on initial and repeat biopsies. Tumor clonality was assessed. Molecular data were compared between men who upgraded and those who did not upgrade to GG ≥ 2 cancer.

RESULTS AND LIMITATIONS

Sixty-six men with median age 64 yr (interquartile range [IQR], 59-69) and prostate-specific antigen 4.9 ng/mL (IQR, 3.3-6.4) underwent repeat sampling of a tracked tumor focus (median interval, 11 mo; IQR, 6-13). IHC-based ERG fusion status was concordant at initial and repeat biopsies in 63 men (95% vs expected 50%, p <  0.001), and RNAseq-based fusion and isoform expression were concordant in nine of 13 (69%) ERG⁺ patients, supporting focal resampling. Among 15 men who upgraded with complete data at both time points, integrated DNA/RNAseq analysis provided evidence of shared clonality in at least five cases. Such cases could reflect initial undersampling, but also support the possibility of clonal temporal progression of low-grade cancer. Our assessment was limited by sample size and use of targeted sequencing.

CONCLUSIONS

Repeat molecular assessment of low-grade tumors suggests that clonal progression could be one mechanism of upgrading. These data underscore the importance of serial tumor assessment in men pursuing AS of low-grade PCa.

PATIENT SUMMARY

We performed targeted rebiopsy and molecular testing of low-grade tumors on active surveillance. Our findings highlight the importance of periodic biopsy as a component of monitoring for cancer upgrading during surveillance.

Incorporating historical models with adaptive Bayesian updates

This article considers Bayesian approaches for incorporating information from a historical model into a current analysis when the historical model includes only a subset of covariates currently of interest. The statistical challenge is 2-fold. First, the parameters in the nested historical model are not generally equal to their counterparts in the larger current model, neither in value nor interpretation. Second, because the historical information will not be equally informative for all parameters in the current analysis, additional regularization may be required beyond that provided by the historical information. We propose several novel extensions of the so-called power prior that adaptively combine a prior based upon the historical information with a variance-reducing prior that shrinks parameter values toward zero. The ideas are directly motivated by our work building mortality risk prediction models for pediatric patients receiving extracorporeal membrane oxygenation (ECMO). We have developed a model on a registry-based cohort of ECMO patients and now seek to expand this model with additional biometric measurements, not available in the registry, collected on a small auxiliary cohort. Our adaptive priors are able to use the information in the original model and identify novel mortality risk factors. We support this with a simulation study, which demonstrates the potential for efficiency gains in estimation under a variety of scenarios.

Sentinel Lymph Node Biopsy in Head and Neck Melanoma: Long-term Outcomes, Prognostic Value, Accuracy, and Safety

OBJECTIVE

To evaluate the long-term outcomes of sentinel lymph node biopsy (SLNB) for head and neck cutaneous melanoma (HNCM).

STUDY DESIGN

Retrospective cohort study.

SETTING

Tertiary academic medical center.

SUBJECTS AND METHODS

Longitudinal review of a 356-patient cohort with HNCM undergoing SLNB from 1997 to 2007.

RESULTS

Descriptive characteristics included the following: age, 53.5 ± 19 years (mean ± SD); sex, 26.8% female; median follow-up, 4.9 years; and Breslow depth, 2.52 ± 1.87 mm. Overall, 75 (21.1%) patients had a positive SLNB. Among patients undergoing completion lymph node dissection following positive SLNB, 20 (27.4%) had at least 1 additional positive nonsentinel lymph node. Eighteen patients with local control and negative SLNB developed regional disease, indicating a false omission rate of 6.4%, including 10 recurrences in previously unsampled basins. Ten-year overall survival (OS) and melanoma-specific survival (MSS) were significantly greater in the negative sentinel lymph node (SLN) cohort (OS, 61% [95% CI, 0.549-0.677]; MSS, 81.9% [95% CI, 0.769-0.873]) than the positive SLN cohort (OS, 31% [95% CI, 0.162-0.677]; MSS, 60.3% [95% CI, 0.464-0.785]) and positive SLN/positive nonsentinel lymph node cohort (OS, 8.4% [95% CI, 0.015-0.474]; MSS, 9.6% [95% CI, 0.017-0.536]). OS was significantly associated with SLN positivity (hazard ratio [HR], 2.39; P < .01), immunosuppression (HR, 2.37; P < .01), angiolymphatic invasion (HR, 1.91; P < .01), and ulceration (HR, 1.86; P < .01). SLN positivity (HR, 3.13; P < .01), angiolymphatic invasion (HR, 3.19; P < .01), and number of mitoses (P = .0002) were significantly associated with MSS. Immunosuppression (HR, 3.01; P < .01) and SLN status (HR, 2.84; P < .01) were associated with recurrence-free survival, and immunosuppression was the only factor significantly associated with regional recurrence (HR, 6.59; P < .01).

CONCLUSIONS

Long-term follow up indicates that SLNB showcases durable accuracy, safety, and prognostic importance for cutaneous HNCM.

TP63 isoform expression is linked with distinct clinical outcomes in cancer

Background

Half of muscle-invasive bladder cancer patients will relapse with metastatic disease and molecular tests to predict relapse are needed. TP63 has been proposed as a prognostic biomarker in bladder cancer, but reports associating it with clinical outcomes are conflicting. Since TP63 is expressed as multiple isoforms, we hypothesized that these conflicting associations with clinical outcome may be explained by distinct opposing effects of differential TP63 isoform expression.

Methods

Using RNA-Seq data from The Cancer Genome Atlas (TCGA), TP63 isoform-level expression was quantified and associated with clinical covariates (e.g. survival, stage) across 8,519 patients from 29 diseases. A comprehensive catalog of TP63 isoforms was assembled using gene annotation databases and de novo discovery in bladder cancer patients. Quantifications and un-annotated TP63 isoforms were validated using quantitative RT-PCR and a separate bladder cancer cohort.

Findings

DNp63 isoform expression was associated with improved bladder cancer patient survival in patients with a luminal subtype (HR = 0.89, CI 0.80–0.99, Cox p = 0.034). Conversely, TAp63 isoform expression was associated with reduced bladder cancer patient survival in patients with a basal subtype (HR = 2.35, CI 1.64–3.37, Cox p < 0.0001). These associations were observed in multiple TCGA disease cohorts and correlated with epidermal differentiation (DNp63) and immune-related (TAp63) gene signatures.

Interpretation

These results comprehensively define TP63 isoform expression in human cancer and suggest that TP63 isoforms are involved in distinct transcriptional programs with opposing effects on clinical outcome.

Burden of chronic diseases among sarcoma survivors treated with anthracycline chemotherapy: results from an observational study

Aim:

Cardiovascular disease is a leading cause of mortality among long-term cancer survivors treated with large total doses of doxorubicin. An increase in coronary artery disease (CAD) among childhood cancer survivors by age 45 has been observed and is driven by primarily anthracycline chemotherapy and to a lesser extent chest radiation that includes the heart in the radiation field. The risk factors and associated chronic diseases (hypertension, etc.) are well known for CAD and can be often prevented or treated, thus reducing the risk of CAD in these patients. We piloted a risk-based survivorship clinic in an academic medical center to characterize the distribution of risk factors for CAD and improve the quality of life in a population of sarcoma survivors treated with doxorubicin.

Methods:

We followed a prospective cohort of sixty-one survivors of bone and soft tissue sarcoma treated with doxorubicin chemotherapy (> 400 mg/m²) and at least 2 years post-therapy attending the sarcoma survivorship clinic. We collected clinical, demographic data, and patient reported outcomes via PROMIS questionnaires annually.

Results:

We demonstrated a high burden of chronic diseases in this population. Among six chronic conditions that are known risk factors for CAD (hypertension, diabetes, obesity, chronic inflammation, kidney disease and dyslipidemia), more than one-fourth (26%, 16/61) of patients had three or more of these risk factors at baseline visit, and 49% (30/61) had two or more.

Conclusion:

The results of this pilot study support the presence of modifiable CAD risk factors in this population of sarcoma survivors. Evidence-based guidelines for high-risk survivors of rare cancers are needed.

Indices of non-ignorable selection bias for proportions estimated from non-probability samples

Rising costs of survey data collection and declining response rates have caused researchers to turn to non-probability samples to make descriptive statements about populations. However, unlike probability samples, non-probability samples may produce severely biased descriptive estimates due to selection bias. The paper develops and evaluates a simple model-based index of the potential selection bias in estimates of population proportions due to non-ignorable selection mechanisms. The index depends on an inestimable parameter ranging from 0 to 1 that captures the amount of deviation from selection at random and is thus well suited to a sensitivity analysis. We describe modified maximum likelihood and Bayesian estimation approaches and provide new and easy-to-use R functions for their implementation. We use simulation studies to evaluate the ability of the proposed index to reflect selection bias in non-probability samples and show how the index outperforms a previously proposed index that relies on an underlying normality assumption. We demonstrate the use of the index in practice with real data from the National Survey of Family Growth.

Accounting for established predictors with the multistep elastic net

Multivariable models for prediction or estimating associations with an outcome are rarely built in isolation. Instead, they are based upon a mixture of covariates that have been evaluated in earlier studies (eg, age, sex, or common biomarkers) and covariates that were collected specifically for the current study (eg, a panel of novel biomarkers or other hypothesized risk factors). For that context, we present the multistep elastic net (MSN), which considers penalized regression with variables that can be qualitatively grouped based upon their degree of prior research support: established predictors vs unestablished predictors. The MSN chooses between uniform penalization of all predictors (the standard elastic net) and weaker penalization of the established predictors in a cross-validated framework and includes the option to impose zero penalty on the established predictors. In simulation studies that reflect the motivating context, we show the comparability or superiority of the MSN over the standard elastic net, the Integrative LASSO with Penalty Factors, the sparse group lasso, and the group lasso, and we investigate the importance of not penalizing the established predictors at all. We demonstrate the MSN to update a prediction model for pediatric ECMO patient mortality.

Ruxolitinib in adult patients with secondary haemophagocytic lymphohistiocytosis: an open-label, single-centre, pilot trial

BACKGROUND

Hemophagocytic lymphohistiocytosis is a cytokine-driven inflammatory syndrome that is associated with substantial morbidity and mortality. Overall survival in adult patients with secondary haemophagocytic lymphohistiocytosis remains suboptimal, and novel therapeutic strategies are needed. The phosphorylation-dependent activation of the Janus family kinases JAK1 and JAK2 are hallmarks of the final common pathway in this disease. We therefore aimed to determine the activity and safety of ruxolitinib, a JAK inhibitor, in adults with secondary haemophagocytic lymphohistiocytosis.

METHODS

We performed an open-label, single-centre, pilot study of ruxolitinib in adults with secondary haemophagocytic lymphohistiocytosis at the University of Michigan Rogel Cancer Center (Ann Arbor, MI, USA). We included patients aged 18 years or more who fulfilled at least five of the eight HLH-2004 criteria for hemophagocytic lymphohistiocytosis. Discontinuation of corticosteroids was not required for enrolment in this study. Patients received oral ruxolitinib (15 mg twice a day) on a continuous 28-day cycle, or until disease progression or unacceptable toxicity. The primary endpoint was overall survival at 2 months from the first dose of ruxolitinib. Secondary endpoints included the assessment of adverse events, response (defined as the assessment of all quantifiable signs and laboratory abnormalities included in the diagnostic criteria for haemophagocytic lymphohistiocytosis), and pharmacodynamic biomarkers. Analyses were done in all treated patients with available data. This study is registered with ClinicalTrials.gov, number NCT02400463, and is still recruiting.

FINDINGS

As of Feb 7, 2019, five patients had been enrolled. The first patient was enrolled in February, 2016. No deaths were recorded, with a median follow-up of 490 days (IQR 190-1075). 2-month overall survival was 100% (95% CI 57-100). Regarding response, resolution of symptoms (either partial or complete) and disease-associated laboratory abnormalities was observed in all five patients. Cytopenias improved in all patients within the first week of treatment, leading to relatively rapid transfusion independence, discontinuation of corticosteroids, and hospital discharge. A single serious adverse event (ie, grade 4 febrile neutropenia) was reported. One patient discontinued treatment because of grade 2 extremity pain and no treatment-related deaths were observed. Improvements in inflammatory markers (eg, ferritin, soluble IL-2 receptor) and T cells and monocytes activation (ie, decreased STAT1 phosphorylation) were observed following treatment.

INTERPRETATION

These preliminary data suggest that ruxolitinib is active, well tolerated, and manageable in the outpatient setting in patients with secondary haemophagocytic lymphohistiocytosis. Given the paucity of effective, non-myelosuppressive therapies, these preliminary findings have important therapeutic implications for patients with haemophagocytic lymphohistiocytosis and other cytokine-release syndromes and warrant further investigation.

FUNDING

National Cancer Institute, the University of Michigan Rogel Cancer Center, and Incyte Corporation.

Default Priors for the Intercept Parameter in Logistic Regressions

In logistic regression, separation occurs when a linear combination of predictors perfectly discriminates the binary outcome. Because finite-valued maximum likelihood parameter estimates do not exist under separation, Bayesian regressions with informative shrinkage of the regression coefficients offer a suitable alternative. Classical studies of separation imply that efficiency in estimating regression coefficients may also depend upon the choice of intercept prior, yet relatively little focus has been given on whether and how to shrink the intercept parameter. Alternative prior distributions for the intercept are proposed that downweight implausibly extreme regions of the parameter space, rendering regression estimates that are less sensitive to separation. Through simulation and the analysis of exemplar datasets, differences across priors stratified by established statistics measuring the degree of separation are quantified. Relative to diffuse priors, these proposed priors generally yield more efficient estimation of the regression coefficients themselves when the data are nearly separated. They are equally efficient in non-separated datasets, making them suitable for default use. Modest differences were observed with respect to out-of-sample discrimination. These numerical studies also highlight the interplay between priors for the intercept and the regression coefficients: findings are more sensitive to the choice of intercept prior when using a weakly informative prior on the regression coefficients than an informative shrinkage prior.

Multicentre retrospective study of intravascular large B-cell lymphoma treated at academic institutions within the United States

Intravascular large B-cell lymphoma (IVLBCL) is a rare entity, with a generally aggressive course that may vary based on geographic presentation. While a United States (US) registry study showed relatively good outcomes with IVLBCL, clinicopathological and treatment data were unavailable. We performed a detailed retrospective review of cases identified at 8 US medical centres, to improve understanding of IVLBCL and inform management. We compiled data retrieved via an Institutional Review Board-approved review of IVLBCL cases identified from 1999 to 2015 at nine academic institutions across the US. We characterized the cohort's clinical status at time of diagnosis, presenting diagnostic and clinical features of the disease, treatment modalities used and overall prognostic data. Our cohort consisted of 54 patients with varying degrees of clinical features. Adjusting for age, better performance status at presentation was associated with increased survival time for the patients diagnosed in vivo (hazard ratio: 2·12, 95% confidence interval 1·28, 3·53). Based on the data we have collected, it would appear that the time interval to diagnosis is a significant contributor to outcomes of patients with IVLBCL.

Predictive models for splenic response to JAK-inhibitor therapy in patients with myelofibrosis

JAK inhibitors for myelofibrosis (MF) reduce spleen size, control constitutional symptoms, and may improve survival. We studied the clinical characteristics of 548 MF patients treated with JAK inhibitors from 2008 to 2016 to better understand predictors of splenic response. Response was defined as a 50% decrease in spleen size at early (3-4 months on therapy) and late (5-12 months) timepoints after therapy initiation. Early response positively correlated with higher doses of JAK inhibitor, baseline spleen size 5-10 cm, and hemoglobin. Early response negatively correlated with baseline spleen size >20 cm and high WBC. The strongest predictor of late response was whether a patient had a response at the earlier timepoint (OR 8.88). Our response models suggest that clinical factors can be used to predict which patients are more likely to respond to JAK inhibitors, and those who do not achieve an early response, i.e. within 3-4 months, should consider alternative treatments.

Prediction of Radiation Esophagitis in Non-Small Cell Lung Cancer Using Clinical Factors, Dosimetric Parameters, and Pretreatment Cytokine Levels

Radiation esophagitis (RE) is a common adverse event associated with radiotherapy for non-small cell lung cancer (NSCLC). While plasma cytokine levels have been correlated with other forms of radiation-induced toxicity, their association with RE has been less well studied. We analyzed data from 126 patients treated on 4 prospective clinical trials. Logistic regression models based on combinations of dosimetric factors [maximum dose to 2 cubic cm (D2cc) and generalized equivalent uniform dose (gEUD)], clinical variables, and pretreatment plasma levels of 30 cytokines were developed. Cross-validated estimates of area under the receiver operating characteristic curve (AUC) and log likelihood were used to assess prediction accuracy. Dose-only models predicted grade 3 RE with AUC values of 0.750 (D2cc) and 0.727 (gEUD). Combining clinical factors with D2cc increased the AUC to 0.779. Incorporating pretreatment cytokine measurements, modeled as direct associations with RE and as potential interactions with the dose-esophagitis association, produced AUC values of 0.758 and 0.773, respectively. D2cc and gEUD correlated with grade 3 RE with odds ratios (ORs) of 1.094/Gy and 1.096/Gy, respectively. Female gender was associated with a higher risk of RE, with ORs of 1.09 and 1.112 in the D2cc and gEUD models, respectively. Older age was associated with decreased risk of RE, with ORs of 0.992/year and 0.991/year in the D2cc and gEUD models, respectively. Combining clinical with dosimetric factors but not pretreatment cytokine levels yielded improved prediction of grade 3 RE compared to prediction by dose alone. Such multifactorial modeling may prove useful in directing radiation treatment planning.

A single center phase II study of ixazomib in patients with relapsed or refractory cutaneous or peripheral T-cell lymphomas

The transcription factor GATA-3, highly expressed in many cutaneous T-cell lymphoma (CTCL) and peripheral T-cell lymphomas (PTCL), confers resistance to chemotherapy in a cell-autonomous manner. As GATA-3 is transcriptionally regulated by NF-κB, we sought to determine the extent to which proteasomal inhibition impairs NF-κB activation and GATA-3 expression and cell viability in malignant T cells. Proteasome inhibition, NF-κB activity, GATA-3 expression, and cell viability were examined in patient-derived cell lines and primary T-cell lymphoma specimens ex vivo treated with the oral proteasome inhibitor ixazomib. Significant reductions in cell viability, NF-κB activation, and GATA-3 expression were observed preclinically in ixazomib-treated cells. Therefore, an investigator-initiated, single-center, phase II study with this agent in patients with relapsed/refractory CTCL/PTCL was conducted. Concordant with our preclinical observations, a significant reduction in NF-κB activation and GATA-3 expression was observed in an exceptional responder following one month of treatment with ixazomib. While ixazomib had limited activity in this small and heterogeneous cohort of patients, inhibition of the NF-κB/GATA-3 axis in a single exceptional responder suggests that ixazomib may have utility in appropriately selected patients or in combination with other agents.

Low-Cost Intervention to Increase Influenza Vaccination Rate at a Comprehensive Cancer Center

Influenza morbidity and mortality can be severe and costly. Vaccination rates remain suboptimal in cancer patients due to provider- and patient-related factors. The objective of this study was to evaluate whether low-cost provider- and patient-focused interventions would increase influenza vaccination rates at the University of Michigan Comprehensive Cancer Center (UMCCC). This quality improvement project included all patients without documentation of influenza vaccination prior to their first outpatient appointment during the 2011-2012 and 2012-2013 influenza seasons. The multi-stepped intervention included provider and patient reminders. Influenza vaccination rates were compiled using CPT-4 codes. Same-day (with appointment) vaccination rates during the intervention seasons were compared to historical (2005-2011 seasons) controls; vaccination rates were also compared to contemporary control population at the University of Michigan Health System (UMHS). Reasons for non-adherence with vaccination were explored. The cumulative same-day vaccination rate in eligible adults was 10.1 % (2011-2012) and 9.4 % (2012-2013) compared to an average 6.9 % during influenza seasons 2005-2011. Based on logistic regression analysis, there was a 37.6 % (95 % CI 35-40.3 %) and 56.1 % (95 % CI 40.9-73 %) relative increase in the adult vaccination rate associated with the intervention, with 399 and 697 additional vaccinations, respectively, for each season. During the 2012-2013 season, the UMCCC adult vaccination rate was higher compared to the remainder of that of the UMHS. The intervention was well accepted by providers. Reasons for no vaccination were provider- and patient-related. Increasing provider and patient awareness with a simple, inexpensive intervention was associated with higher influenza vaccination rates at a large academic cancer center. The intervention is permanently implemented during influenza seasons.

Genetic anticipation in Swedish Lynch syndrome families

Among hereditary colorectal cancer predisposing syndromes, Lynch syndrome (LS) caused by mutations in DNA mismatch repair genes MLH1, MSH2, MSH6 or PMS2 is the most common. Patients with LS have an increased risk of early onset colon and endometrial cancer, but also other tumors that generally have an earlier onset compared to the general population. However, age at first primary cancer varies within families and genetic anticipation, i.e. decreasing age at onset in successive generations, has been suggested in LS. Anticipation is a well-known phenomenon in e.g neurodegenerative diseases and several reports have studied anticipation in heritable cancer. The purpose of this study is to determine whether anticipation can be shown in a nationwide cohort of Swedish LS families referred to the regional departments of clinical genetics in Lund, Stockholm, Linköping, Uppsala and Umeå between the years 1990–2013. We analyzed a homogenous group of mutation carriers, utilizing information from both affected and non-affected family members. In total, 239 families with a mismatch repair gene mutation (96 MLH1 families, 90 MSH2 families including one family with an EPCAM–MSH2 deletion, 39 MSH6 families, 12 PMS2 families, and 2 MLH1+PMS2 families) comprising 1028 at-risk carriers were identified among the Swedish LS families, of which 1003 mutation carriers had available follow-up information and could be included in the study. Using a normal random effects model (NREM) we estimate a 2.1 year decrease in age of diagnosis per generation. An alternative analysis using a mixed-effects Cox proportional hazards model (COX-R) estimates a hazard ratio of exp(0.171), or about 1.19, for age of diagnosis between consecutive generations. LS-associated gene-specific anticipation effects are evident for MSH2 (2.6 years/generation for NREM and hazard ratio of 1.33 for COX-R) and PMS2 (7.3 years/generation and hazard ratio of 1.86). The estimated anticipation effects for MLH1 and MSH6 are smaller.

Genetic anticipation is a phenomenon where symptoms of a hereditary disease appear at an earlier age and/or are more severe in successive generations. In genetic disorders such as Fragile X syndrome, Myotonic dystrophy type 1 and Huntington disease, anticipation is caused by the expansion of unstable trinucleotide repeats during meiosis. Anticipation is also reported to occur in some hereditary cancers though the underlying mechanism behind this observation is unknown. Several studies have investigated anticipation in Lynch syndrome, the most common hereditary colorectal cancer syndrome, yet there is a debate concerning whether anticipation occurs and what underlying mechanism there is. The objective of this project is to study if anticipation is part of the clinical picture in Swedish families with LS, with the long term goal to enable better prediction of age at onset in family members. Our results suggest that anticipation occurs in families with mutation in MSH2 and PMS2, while the evidence is equivocal for MLH1 and MSH6.

Radiation-induced lung toxicity in non-small-cell lung cancer: Understanding the interactions of clinical factors and cytokines with the dose-toxicity relationship

BACKGROUND AND PURPOSE

Current methods to estimate risk of radiation-induced lung toxicity (RILT) rely on dosimetric parameters. We aimed to improve prognostication by incorporating clinical and cytokine data, and to investigate how these factors may interact with the effect of mean lung dose (MLD) on RILT.

MATERIALS AND METHODS

Data from 125 patients treated from 2004 to 2013 with definitive radiotherapy for stages I-III NSCLC on four prospective clinical trials were analyzed. Plasma levels of 30 cytokines were measured pretreatment, and at 2 and 4weeks midtreatment. Penalized logistic regression models based on combinations of MLD, clinical factors, and cytokine levels were developed. Cross-validated estimates of log-likelihood and area under the receiver operating characteristic curve (AUC) were used to assess accuracy.

RESULTS

In prognosticating grade 3 or greater RILT by MLD alone, cross-validated log-likelihood and AUC were -28.2 and 0.637, respectively. Incorporating clinical features and baseline cytokine levels increased log-likelihood to -27.6 and AUC to 0.669. Midtreatment cytokine data did not further increase log-likelihood or AUC. Of the 30 cytokines measured, higher levels of 13 decreased the effect of MLD on RILT, corresponding to a lower odds ratio for RILT per Gy MLD, while higher levels of 4 increased the association.

CONCLUSIONS

Although the added prognostic benefit from cytokine data in our model was modest, understanding how clinical and biologic factors interact with the MLD-RILT relationship represents a novel framework for understanding and investigating the multiple factors contributing to radiation-induced toxicity.

Efficacy of Staged Excision With Permanent Section Margin Control for Cutaneous Head and Neck Melanoma

Importance

Melanoma arising in chronically photodamaged skin, especially on the head and neck, is often characterized by poorly defined clinical margins and unpredictable occult extension. Staged excision techniques have been described to treat these challenging melanomas.

Objective

To investigate the local recurrence rates and margin to clearance end points using staged excision with comprehensive hematoxylin-eosin-stained permanent section margin control.

Design, Setting, and Participants

In this observational cohort study performed from October 8, 1997, to December 31, 2006, with a median follow-up of 9.3 years, 806 patients with melanoma on the head and neck, where clinical occult extension is common, were studied at an academic medical center.

Interventions

Staged excision with comprehensive hematoxylin-eosin-stained permanent section margin control commonly known as the square technique.

Main Outcomes and Measures

Local recurrence rates and margin to clearance end points.

Results

A total of 806 patients (276 women [34.2%]; 805 white [99.9%]) with a median age at the time of first staged excision procedure of 65 years (range, 20-94 years) participated in the study. The estimated local recurrence rates were 1.4% at 5 years, 1.8% at 7.5 years, and 2.2% at 10 years. For each 50-mm2 increase in the size of the clinical lesion, there was a 9% increase in the rate of local recurrence (hazard ratio, 1.09; 95% CI, 1.02-1.15; P = .02). The mean (SD) margin from lesion to clearance for melanoma in situ was 9.3 (5.1) mm compared with 13.7 (5.9) mm for invasive melanoma. For melanoma in situ, margins were clear after 5 mm or less in 232 excisions (41.1%) and after 10 mm or less in 420 excisions (74.5%). For invasive melanoma, margins were clear after 5 mm or less in 8 excisions (3.0%) and after 10 mm or less in 141 excisions (52.2%).

Conclusions and Relevance

Staged excision with comprehensive permanent section margin control of melanomas arising in chronically sun-damaged skin on the head and neck has favorable recurrence rates when melanoma margins are difficult to assess, and recurrence rates are high with traditional techniques.

Dopamine D2/D3 imbalance during migraine attack and allodynia in vivo

OBJECTIVE

To evaluate in vivo the dynamics of endogenous dopamine (DA) neurotransmission during migraine ictus with allodynia.

METHODS

We examined 8 episodic migraineurs and 8 healthy controls (HC) using PET with [¹¹C]raclopride. The uptake measure of [¹¹C]raclopride, nondisplaceable binding potential (BP_ND), would increase when there was a reduction in endogenous DA release. The opposite is true for a decrease in [¹¹C]raclopride BP_ND. Patients were scanned twice: one PET session was during a spontaneous migraine ictus at rest, followed by a sustained thermal pain threshold (STPT) challenge on the trigeminal region, eliciting an allodynia experience; another was during interictal phase.

RESULTS

Striatal BP_ND of [¹¹C]raclopride in migraineurs did not differ from HC. We found a significant increase in [¹¹C]raclopride BP_ND in the striatum region of migraineurs during both headache attack and allodynia relative to interictal phase. However, when compared to the migraine attack at rest, migraineurs during the STPT challenge had a significant sudden reduction in [¹¹C]raclopride BP_ND in the insula. Such directional change was also observed in the caudate of HC relative to the interictal phase during challenge. Furthermore, ictal changes in [¹¹C]raclopride BP_ND in migraineurs at rest were positively correlated with the chronicity of migraine attacks, and negatively correlated with the frequency during challenge.

CONCLUSIONS

Our findings demonstrate that there is an imbalanced uptake of [¹¹C]raclopride during the headache attack and ictal allodynia, which indicates reduction and fluctuation in ictal endogenous DA release in migraineurs. Moreover, the longer the history and recurrence of migraine attacks, the lower the ictal endogenous DA release.

Hospital-level variation in inpatient cost among children receiving extracorporeal membrane oxygenation

OBJECTIVE

Pediatric extracorporeal membrane oxygenation (ECMO) varies in the way care is provided from hospital to hospital. This variability in hospital ECMO care can be represented by the variation in ECMO costs. We hypothesized that hospitals will demonstrate large variations in case-mix-adjusted ECMO inpatient costs for children requiring ECMO and higher volume hospitals will have lower associated costs.

METHODS

We retrospectively analyzed the inpatient cost of children receiving ECMO in 2006, 2009 and 2012, using the Healthcare Cost and Utilization Project Kids' Inpatient Database. We used a hierarchical linear regression model and the intraclass correlation coefficient to quantify how much of the difference in ECMO inpatient costs was associated with the hospital where a child received care. To do this, we adjusted for patient factors, hospital factors and potentially modifiable factors such as complications, procedures and length of stay.

RESULTS

The median inflation-adjusted inpatient costs for children requiring ECMO were $183,000, $240,000 and $241,000 in years 2006, 2009 and 2012, respectively. The largest median cost for ECMO cases in a given hospital in a given year ($690,000) was more than 11 times that of the smallest median cost ($60,000). After case-mix adjustment, 27% of the variation in inpatient costs was associated with the hospital where ECMO care was provided. Average hospital costs were not associated with hospital ECMO volume.

CONCLUSIONS

The large variation in ECMO inpatient costs between hospitals suggests great variation in care between hospitals, which is important because hospitals have a co-existing variation in ECMO survival rates.

Lower Incidence of Esophagitis in the Elderly Undergoing Definitive Radiation Therapy for Lung Cancer

INTRODUCTION

Most patients with lung cancer are elderly and poorly represented in randomized clinical trials. They are often undertreated because of concerns about their ability to tolerate aggressive treatment. We tested the hypothesis that elderly patients undergoing definitive lung radiation might tolerate treatment differently than younger patients.

METHODS

A total of 125 patients who underwent definitive lung radiotherapy were identified from a prospective institutional database (University of Michigan cohort). Logistic regression modeling was performed to assess the impact of age on esophagitis grade 2 or higher or grade 2 or higher and pneumonitis grade 3 or higher or grade 2 or higher, with adjustment for esophageal and lung dose, respectively, as well as for chemotherapy utilization, smoking status, and performance status. The analysis was validated in a large cohort of 691 patients from the Michigan Radiation Oncology Quality Consortium registry, an independent statewide prospective database.

RESULTS

In the University of Michigan cohort, multivariable regression models revealed a significant inverse correlation between age and rate of esophagitis for both toxicity levels, (adjusted OR = 0.93 for both models and 95% confidence intervals of 0.88-0.98 and 0.87-0.99), with areas under the curve of 0.747 and 0.721, respectively, demonstrating good fit. This same association was noted in the Michigan Radiation Oncology Quality Consortium cohort. There was no significant association between age and pneumonitis.

CONCLUSIONS

There is a lower incidence of esophagitis with increasing age even after adjustment for use of chemotherapy. This is a novel finding in thoracic oncology. No age dependence was noted for pulmonary toxicity. The elderly are able to tolerate definitive thoracic radiation well and should be offered this option when clinically warranted.

Colony-Stimulating Factor-1 Receptor Is Required for Nurse-like Cell Survival in Chronic Lymphocytic Leukemia

PURPOSE

Monocytes and their progeny are abundant constituents of the tumor microenvironment in lymphoproliferative disorders, including chronic lymphocytic leukemia (CLL). Monocyte-derived cells, including nurse-like cells (NLC) in CLL, promote lymphocyte proliferation and survival, confer resistance to chemotherapy, and are associated with more rapid disease progression. Colony-stimulating factor-1 receptor (CSF-1R) regulates the homeostatic survival of tissue-resident macrophages. Therefore, we sought to determine whether CSF-1R is similarly required for NLC survival.

EXPERIMENTAL DESIGN

CSF-1R expression by NLC was examined by flow cytometry and IHC. CSF-1R blocking studies were performed using an antagonistic mAb to examine its role in NLC generation and in CLL survival. A rational search strategy was performed to identify a novel tyrosine kinase inhibitor (TKI) targeting CSF-1R. The influence of TKI-mediated CSF-1R inhibition on NLC and CLL viability was examined.

RESULTS

We demonstrated that the generation and survival of NLC in CLL is dependent upon CSF-1R signaling. CSF-1R blockade is associated with significant depletion of NLC and consequently inhibits CLL B-cell survival. We found that the JAK2/FLT3 inhibitor pacritinib suppresses CSF-1R signaling, thereby preventing the generation and survival of NLC and impairs CLL B-cell viability.

CONCLUSIONS

CSF-1R is a novel therapeutic target that may be exploited in lymphoproliferative disorders, like CLL, that are dependent upon lymphoma-associated macrophages. Clin Cancer Res; 22(24); 6118-28. ©2016 AACR.

Development and validation of the pediatric risk estimate score for children using extracorporeal respiratory support (Ped-RESCUERS)

PURPOSE

To develop and validate the Pediatric Risk Estimation Score for Children Using Extracorporeal Respiratory Support (Ped-RESCUERS). Ped-RESCUERS is designed to estimate the in-hospital mortality risk for children prior to receiving respiratory extracorporeal membrane oxygenation (ECMO) support.

METHODS

This study used data from an international registry of patients aged 29 days to less than 18 years who received ECMO support from 2009 to 2014. We divided the registry into development and validation datasets by calendar date. Candidate variables were selected for model inclusion if the variable independently changed the mortality risk by at least 2 % in a Bayesian logistic regression model with in-hospital mortality as the outcome. We characterized the model's ability to discriminate mortality with the area under curve (AUC) of the receiver operating characteristic.

RESULTS

From 2009 to 2014, 2458 non-neonatal children received ECMO for respiratory support, with a mortality rate of 39.8 %. The development dataset contained 1611 children receiving ECMO support from 2009 to 2012. The model included the following variables: pre-ECMO pH, pre-ECMO arterial partial pressure of carbon dioxide, hours of intubation prior to ECMO support, hours of admission at ECMO center prior to ECMO support, ventilator type, mean airway pressure, pre-ECMO use of milrinone, and a diagnosis of pertussis, asthma, bronchiolitis, or malignancy. The validation dataset included 438 children receiving ECMO support from 2013 to 2014. The Ped-RESCUERS model from the development dataset had an AUC of 0.690, and the validation dataset had an AUC of 0.634.

CONCLUSIONS

Ped-RESCUERS provides a novel measure of pre-ECMO mortality risk. Future studies should seek external validation and improved discrimination of this mortality prediction tool.

Is the problem list in the eye of the beholder? An exploration of consistency across physicians

OBJECTIVE

Quantify the variability of patients' problem lists - in terms of the number, type, and ordering of problems - across multiple physicians and assess physicians' criteria for organizing and ranking diagnoses.

MATERIALS AND METHODS

In an experimental setting, 32 primary care physicians generated and ordered problem lists for three identical complex internal medicine cases expressed as detailed 2- to 4-page abstracts and subsequently expressed their criteria for ordering items in the list. We studied variability in problem list length. We modified a previously validated rank-based similarity measure, with range of zero to one, to quantify agreement between pairs of lists and calculate a single consensus problem list that maximizes agreement with each physician. Physicians' reasoning for the ordering of the problem lists was recorded.

RESULTS

Subjects' problem lists were highly variable. The median problem list length was 8 (range: 3-14) for Case A, 10 (range: 4-20) for Case B, and 7 (range: 3-13) for Case C. The median indices of agreement - taking into account the length, content, and order of lists - over all possible physician pairings was 0.479, 0.371, 0.509, for Cases A, B, and C, respectively. The median agreements between the physicians' lists and the consensus list for each case were 0.683, 0.581, and 0.697 (for Cases A, B, and C, respectively).Out of a possible 1488 pairings, 2 lists were identical. Physicians most frequently ranked problem list items based on their acuity and immediate threat to health.

CONCLUSIONS

The problem list is a physician's mental model of a patient's health status. These mental models were found to vary significantly between physicians, raising questions about whether problem lists created by individual physicians can serve their intended purpose to improve care coordination.

Alpha/beta (α/β) ratio for prostate cancer derived from external beam radiotherapy and brachytherapy boost

OBJECTIVE

There is disagreement regarding the value of the α/β ratio for prostate cancer. Androgen deprivation therapy (ADT) may dominate the effects of dose fractionation on prostate-specific antigen (PSA) response and confound estimates of the α/β ratio. We estimate this ratio from combined data on external beam radiation therapy (EBRT) and brachytherapy (BT)-treated patients, providing a range of doses per fraction, while accounting for the effects of ADT.

METHODS

We analyse data on 289 patients with local prostate cancer treated with EBRT (2 Gy per fraction) or EBRT plus one or two BT boosts of 10 Gy each. The timing of ADT was heterogeneous. We develop statistical models to estimate the α/β ratio based upon PSA measurements at 1 year as a surrogate for the surviving fraction of cancer cells as well as combined biochemical + clinical recurrence-free survival (bcRFS), controlling for ADT.

RESULTS

For the PSA-based end point, the α/β ratio estimate is 7.7 Gy [95% confidence interval (CI): 4.1 to 12.5]. Based on the bcRFS end point, the estimate is 18.0 Gy (95% CI: 8.2 to ∞).

CONCLUSION

Our model-based estimates of the α/β ratio, which account for the effects of ADT and other important confounders, are higher than some previous estimates.

ADVANCES IN KNOWLEDGE

Although dose inhomogeneities and other limitations may limit the scope of our findings, the data suggest caution regarding the assumptions of the α/β ratio for prostate cancer in some clinical environments.

Tests for Gene-Environment Interactions and Joint Effects With Exposure Misclassification

The number of methods for genome-wide testing of gene-environment (G-E) interactions continues to increase, with the aim of discovering new genetic risk factors and obtaining insight into the disease-gene-environment relationship. The relative performance of these methods, assessed on the basis of family-wise type I error rate and power, depends on underlying disease-gene-environment associations, estimates of which may be biased in the presence of exposure misclassification. This simulation study expands on a previously published simulation study of methods for detecting G-E interactions by evaluating the impact of exposure misclassification. We consider 7 single-step and modular screening methods for identifying G-E interaction at a genome-wide level and 7 joint tests for genetic association and G-E interaction, for which the goal is to discover new genetic susceptibility loci by leveraging G-E interaction when present. In terms of statistical power, modular methods that screen on the basis of the marginal disease-gene relationship are more robust to exposure misclassification. Joint tests that include main/marginal effects of a gene display a similar robustness, which confirms results from earlier studies. Our results offer an increased understanding of the strengths and limitations of methods for genome-wide searches for G-E interaction and joint tests in the presence of exposure misclassification.

A Small-Sample Choice of the Tuning Parameter in Ridge Regression

We propose new approaches for choosing the shrinkage parameter in ridge regression, a penalized likelihood method for regularizing linear regression coefficients, when the number of observations is small relative to the number of parameters. Existing methods may lead to extreme choices of this parameter, which will either not shrink the coefficients enough or shrink them by too much. Within this "small-n, large-p" context, we suggest a correction to the common generalized cross-validation (GCV) method that preserves the asymptotic optimality of the original GCV. We also introduce the notion of a "hyperpenalty", which shrinks the shrinkage parameter itself, and make a specific recommendation regarding the choice of hyperpenalty that empirically works well in a broad range of scenarios. A simple algorithm jointly estimates the shrinkage parameter and regression coefficients in the hyperpenalized likelihood. In a comprehensive simulation study of small-sample scenarios, our proposed approaches offer superior prediction over nine other existing methods.

A statistical evaluation of dose expansion cohorts in phase I clinical trials

BACKGROUND

Phase I trials often include a dose expansion cohort (DEC), in which additional patients are treated at the estimated maximum tolerated dose (MTD) after dose escalation, with the goal of ensuring that data are available from more than six patients at a single dose level. However, protocols do not always detail how, or even if, the additional toxicity data will be used to reanalyze the MTD or whether observed toxicity in the DEC will warrant changing the assigned dose. A DEC strategy has not been statistically justified.

METHODS

We conducted a simulation study of two phase I designs: the "3+3" and the Continual Reassessment Method (CRM). We quantified how many patients are assigned the true MTD using a 10 to 20 patient DEC and how a sensible reanalysis using the DEC changes the probability of selecting the true MTD. We compared these results with those from an equivalently sized larger CRM that does not include a DEC.

RESULTS

With either the 3+3 or CRM, reanalysis with the DEC increased the probability of identifying the true MTD. However, a large CRM without a DEC was more likely to identify the true MTD while still treating 10 or 15 patients at this dose level.

CONCLUSIONS

Where feasible, a CRM design with no explicit DEC is preferred to designs that fix a dose for all patients in a DEC.

The impact of exposure-biased sampling designs on detection of gene-environment interactions in case-control studies with potential exposure misclassification

With limited funding and biological specimen availability, choosing an optimal sampling design to maximize power for detecting gene-by-environment (G-E) interactions is critical. Exposure-enriched sampling is often used to select subjects with rare exposures for genotyping to enhance power for tests of G-E effects. However, exposure misclassification (MC) combined with biased sampling can affect characteristics of tests for G-E interaction and joint tests for marginal association and G-E interaction. Here, we characterize the impact of exposure-biased sampling under conditions of perfect exposure information and exposure MC on properties of several methods for conducting inference. We assess the Type I error, power, bias, and mean squared error properties of case-only, case-control, and empirical Bayes methods for testing/estimating G-E interaction and a joint test for marginal G (or E) effect and G-E interaction across three biased sampling schemes. Properties are evaluated via empirical simulation studies. With perfect exposure information, exposure-enriched sampling schemes enhance power as compared to random selection of subjects irrespective of exposure prevalence but yield bias in estimation of the G-E interaction and marginal E parameters. Exposure MC modifies the relative performance of sampling designs when compared to the case of perfect exposure information. Those conducting G-E interaction studies should be aware of exposure MC properties and the prevalence of exposure when choosing an ideal sampling scheme and method for characterizing G-E interactions and joint effects.

Increasing efficiency for estimating treatment-biomarker interactions with historical data

Detecting a treatment-biomarker interaction, which is a task better suited for large sample sizes, in a phase II trial, which has a small sample size, is challenging. In this paper, we investigate how two plausibly available sources of historical data may contain partial information to help estimate the treatment-biomarker interaction parameter in a randomized phase II study. The parameter is not identified in either historical dataset alone; nonetheless, both can provide some information about the parameter and, consequently, increase the precision of its estimate. To illustrate the potential for gains in efficiency and implications for the design of the study, we consider Gaussian outcomes and biomarker data and calculate the asymptotic variance using the expected Fisher information matrix. We quantify the gain in efficiency both through a numerical study and, in a simplified setting, insights derived from an algebraic development of the problem. We find that a non-negligible gain in precision is possible, even if the historical and prospective data do not arise from identical underlying models.