Jared C. Foster

Outcomes evaluation of a weekly nurse practitioner-managed symptom management clinic for patients with head and neck cancer treated with chemoradiotherapy.

PURPOSE/OBJECTIVES To determine whether improved monitoring through close follow-up with a nurse practitioner (NP) could enhance treatment compliance and decrease frequency of hospitalizations. DESIGN Retrospective chart review. SETTING An academic National Cancer Institute-designated comprehensive cancer center. SAMPLE 151 patients aged 45-65 years diagnosed with stage III or IV oropharyngeal cancer. METHODS Patients were nonrandomized to one of two groups: a prechemotherapy clinic group and a weekly NP-led clinic group. After examination of descriptive statistics, multiple linear and logistic regressions were used to compare groups across patient outcomes. MAIN RESEARCH VARIABLES Hospitalization, chemotherapy dose deviations, and chemotherapy treatment completion. FINDINGS The average number of visits during traditional treatment was three and, after initiation of the NP-led clinic, the number was six. The hospitalization rate was 28% in the traditional clinic group compared to 12% in the NP-led group. The rate of chemotherapy dose deviations was 48% in the traditional clinic group compared to 6% in the NP-led clinic group. Forty-six percent of patients in the traditional clinic group received the full seven scheduled doses of chemotherapy compared to 90% of patients seen in the NP-led clinic group. CONCLUSIONS A weekly NP-led symptom management clinic reduces rates of hospitalization and chemotherapy dose deviations and increases chemotherapy completion in patients receiving intensive chemoradiotherapy for oropharyngeal cancer. IMPLICATIONS FOR NURSING Patients receiving chemoradiotherapy benefit from close monitoring for toxicities by NPs to successfully complete their treatment and avoid hospitalization. KNOWLEDGE TRANSLATION Early interventions to manage toxicities in patients with head and neck cancer can improve outcomes. NPs are in a key position to manage these toxicities and, when symptoms are controlled, costs are reduced.

Simple subgroup approximations to optimal treatment regimes from randomized clinical trial data.

We consider the use of randomized clinical trial (RCT) data to identify simple treatment regimes based on some subset of the covariate space, A. The optimal subset, A, is selected by maximizing the expected outcome under a treat-if-in-A regime, and is restricted to be a simple, as it is desirable that treatment decisions be made with only a limited amount of patient information required. We consider a two-stage procedure. In stage 1, non-parametric regression is used to estimate treatment effects for each subject, and in stage 2 these treatment effect estimates are used to systematically evaluate many subgroups of a simple, prespecified form to identify A. The proposed methods were found to perform favorably compared with two existing methods in simulations, and were applied to prehypertension data from an RCT.

Reader reaction to “A robust method for estimating optimal treatment regimes” by Zhang et al. (2012)

A recent article (Zhang et al., 2012, Biometrics 168, 1010-1018) compares regression based and inverse probability based methods of estimating an optimal treatment regime and shows for a small number of covariates that inverse probability weighted methods are more robust to model misspecification than regression methods. We demonstrate that using models that fit the data better reduces the concern about non-robustness for the regression methods. We extend the simulation study of Zhang et al. (2012, Biometrics 168, 1010-1018), also considering the situation of a larger number of covariates, and show that incorporating random forests into both regression and inverse probability weighted based methods improves their properties.

Variable selection in monotone single‐index models via the adaptive LASSO

We consider the problem of variable selection for monotone single-index models. A single-index model assumes that the expectation of the outcome is an unknown function of a linear combination of covariates. Assuming monotonicity of the unknown function is often reasonable and allows for more straightforward inference. We present an adaptive LASSO penalized least squares approach to estimating the index parameter and the unknown function in these models for continuous outcome. Monotone function estimates are achieved using the pooled adjacent violators algorithm, followed by kernel regression. In the iterative estimation process, a linear approximation to the unknown function is used, therefore reducing the situation to that of linear regression and allowing for the use of standard LASSO algorithms, such as coordinate descent. Results of a simulation study indicate that the proposed methods perform well under a variety of circumstances and that an assumption of monotonicity, when appropriate, noticeably improves performance. The proposed methods are applied to data from a randomized clinical trial for the treatment of a critical illness in the intensive care unit.

Long-Term Effects of Pre-Placement Risk Factors on Children’s Psychological Symptoms and Parenting Stress Among Families Adopting Children From Foster Care

This exploratory longitudinal study examined behavioral outcomes and parenting stress among families with children adopted from foster care, taking into account environmental and biological risk factors. Child internalizing and externalizing problems and parenting stress were assessed in 82 adopted children and their families at 2 months post-placement, 12 months post-placement, and then yearly until 5 years post-placement. A history of abuse/neglect predicted significantly higher externalizing and internalizing problems at a borderline level of statistical significance. In the initial stages after placement, externalizing problems were significantly higher among children who were 4 years or older at placement versus those who were younger than 4, although differences were no longer significant 5 years post-placement. Statistical trends in parenting stress reflected reduced stress in the first 12 months followed by a plateau for parents who adopted older children and greater stress for parents who adopted younger children. Familiar limitations for observational cohort data apply. Nonetheless, the availability of longitudinal follow-up on a sizable sample of children adopted from foster care adds insight to the psychological dynamics for adoptive families and suggests that families of children adopted from the foster care system may have unique needs for ongoing support around behavioral issues.

A phase II trial evaluating weekly docetaxel and capecitabine in patients with metastatic or advanced, locally recurrent head and neck cancers.

ABSTRACT We conducted a phase II study to determine the response rate and toxicity of weekly docetaxel and a flat dose capecitabine (days 5–18 of the 28-day cycle) in patients with incurable locally recurrent or metastatic head and neck cancers. The responses at 4 months were analyzed among 36 patients. Although the response rate was modest (11%), the 6.5 months estimated median survival was comparable to the standard platinum and 5-FU combination regimens. Major grade 3 and 4 toxicities included lymphopenia, infection, and fatigue. In view of low efficacy, this particular regimen does not appear to warrant further study.

Identifying subgroups of enhanced predictive accuracy from longitudinal biomarker data by using tree-based approaches: applications to fetal growth

Longitudinal monitoring of biomarkers is often helpful for predicting disease or a poor clinical outcome. In this paper, We consider the prediction of both large and small-for-gestational-age births using longitudinal ultrasound measurements, and attempt to identify subgroups of women for whom prediction is more (or less) accurate, should they exist. We propose a tree-based approach to identifying such subgroups, and a pruning algorithm which explicitly incorporates a desired type-I error rate, allowing us to control the risk of false discovery of subgroups. The proposed methods are applied to data from the Scandinavian Fetal Growth Study, and are evaluated via simulations.

Cost-Effectiveness Analysis of Monthly Zoledronic Acid, Zoledronic Acid Every 3 Months, and Monthly Denosumab in Women With Breast Cancer and Skeletal Metastases: CALGB 70604 (Alliance)

Purpose Skeletal-related events (SREs) such as pathologic fracture, spinal cord compression, or the necessity for radiation or surgery to bone metastasis cause considerable morbidity, decrements in quality of life, and costs to the health care system. The results of a recent large randomized trial (Cancer and Leukemia Group B/Alliance for Clinical Trials in Oncology [CALGB/Alliance 70604]) showed that zoledronic acid (ZA) every 3 months was noninferior to monthly ZA in reducing the risks of SREs. We sought to determine the cost-effectiveness (CE) of monthly ZA, ZA every 3 months, and monthly denosumab in women with breast cancer and skeletal metastases. Methods Using a Markov model, costs per SRE avoided were calculated for the three treatments. Sensitivity analyses were performed where denosumab SRE probabilities were assumed to be 50%, 75%, and 90% lower than the ZA SRE probabilities. Quality-adjusted life-years were also calculated. The analysis was from the US payer perspective. Results The mean costs of the denosumab treatment strategy are nine-fold higher than generic ZA every 3 months. Quality-adjusted life-years were virtually identical in all the three treatment arms; hence, the optimal treatment would be ZA every 3 months because it was the least costly treatment. The sensitivity analyses showed that relative to ZA every 3 months, the incremental costs per mean SRE avoided for denosumab ranged from

Reader Reaction to “A Robust Method for Estimating OptimalTreatment Regimes” by

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Reader reaction to “A robust method for estimating optimal treatment regimes” by Zhang et al. (2012): Reader Reaction to “A Robust Method for Estimating Optimal Treatment Regimes” by Zhang et al. (2012)

347,655. Conclusion ZA every 3 months was more CE in reducing the risks of SRE than monthly denosumab. This analysis was one of the first to incorporate the costs of generic ZA and one of the first independent CE analyses not sponsored by either Novartis or Amgen, the makers of ZA and denosumab, respectively. ZA every 3 months is the more CE option and more reasonable alternative to monthly denosumab.