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OBJECTIVECurrent costs associated with spine care are unsustainable. Productivity loss and time away from work for patients who were once gainfully employed contributes greatly to the financial burden experienced by individuals and, more broadly, society. Therefore, it is vital to identify the factors associated with return to work (RTW) after lumbar spine surgery. In this analysis, the authors used data from a national prospective outcomes registry to create a predictive model of patients’ ability to RTW after undergoing lumbar spine surgery for degenerative spine disease.METHODSData from 4694 patients who underwent elective spine surgery for degenerative lumbar disease, who had been employed preoperatively, and who had completed a 3-month follow-up evaluation, were entered into a prospective, multicenter registry. Patient-reported outcomes—Oswestry Disability Index (ODI), numeric rating scale (NRS) for back pain (BP) and leg pain (LP), and EQ-5D scores—were recorded at baseline and at 3 months postoperatively. The time to RTW was defined as the period between operation and date of returning to work. A multivariable Cox proportional hazards regression model, including an array of preoperative factors, was fitted for RTW. The model performance was measured using the concordance index (c-index).RESULTSEighty-two percent of patients (n = 3855) returned to work within 3 months postoperatively. The risk-adjusted predictors of a lower likelihood of RTW were being preoperatively employed but not working at the time of presentation, manual labor as an occupation, worker’s compensation, liability insurance for disability, higher preoperative ODI score, higher preoperative NRS-BP score, and demographic factors such as female sex, African American race, history of diabetes, and higher American Society of Anesthesiologists score. The likelihood of a RTW within 3 months was higher in patients with higher education level than in those with less than high school–level education. The c-index of the model’s performance was 0.71.CONCLUSIONSThis study presents a novel predictive model for the probability of returning to work after lumbar spine surgery. Spine care providers can use this model to educate patients and encourage them in shared decision-making regarding the RTW outcome. This evidence-based decision support will result in better communication between patients and clinicians and improve postoperative recovery expectations, which will ultimately increase the likelihood of a positive RTW trajectory.

OBJECTIVEQuality and outcomes registry platforms lie at the center of many emerging evidence-driven reform models. Specifically, clinical registry data are progressively informing health care decision-making. In this analysis, the authors used data from a national prospective outcomes registry (the Quality Outcomes Database) to develop a predictive model for 12-month postoperative pain, disability, and quality of life (QOL) in patients undergoing elective lumbar spine surgery.METHODSIncluded in this analysis were 7618 patients who had completed 12 months of follow-up. The authors prospectively assessed baseline and 12-month patient-reported outcomes (PROs) via telephone interviews. The PROs assessed were those ascertained using the Oswestry Disability Index (ODI), EQ-5D, and numeric rating scale (NRS) for back pain (BP) and leg pain (LP). Variables analyzed for the predictive model included age, gender, body mass index, race, education level, history of prior surgery, smoking status, comorbid conditions, American Society of Anesthesiologists (ASA) score, symptom duration, indication for surgery, number of levels surgically treated, history of fusion surgery, surgical approach, receipt of workers’ compensation, liability insurance, insurance status, and ambulatory ability. To create a predictive model, each 12-month PRO was treated as an ordinal dependent variable and a separate proportional-odds ordinal logistic regression model was fitted for each PRO.RESULTSThere was a significant improvement in all PROs (p < 0.0001) at 12 months following lumbar spine surgery. The most important predictors of overall disability, QOL, and pain outcomes following lumbar spine surgery were employment status, baseline NRS-BP scores, psychological distress, baseline ODI scores, level of education, workers’ compensation status, symptom duration, race, baseline NRS-LP scores, ASA score, age, predominant symptom, smoking status, and insurance status. The prediction discrimination of the 4 separate novel predictive models was good, with a c-index of 0.69 for ODI, 0.69 for EQ-5D, 0.67 for NRS-BP, and 0.64 for NRS-LP (i.e., good concordance between predicted outcomes and observed outcomes).CONCLUSIONSThis study found that preoperative patient-specific factors derived from a prospective national outcomes registry significantly influence PRO measures of treatment effectiveness at 12 months after lumbar surgery. Novel predictive models constructed with these data hold the potential to improve surgical effectiveness and the overall value of spine surgery by optimizing patient selection and identifying important modifiable factors before a surgery even takes place. Furthermore, these models can advance patient-focused care when used as shared decision-making tools during preoperative patient counseling.

Abstract Introduction Multiple intravenous doses of ponezumab, an anti‐amyloid antibody, were evaluated in subjects with mild‐to‐moderate Alzheimer's disease (AD). Methods In part A, 77 subjects were randomized to ponezumab 0.1, 0.5, or 1 mg/kg (75 treated) and 26 to placebo (24 treated). In part B, 63 subjects were randomized and treated with ponezumab 3 or 8.5 mg/kg and 32 with placebo. Subjects received 10 infusions over 18 months and were followed for 6 months thereafter. Results Ponezumab was generally safe and well tolerated. Most common adverse events were fall (16.7% ponezumab, 21.4% placebo), headache (13.8%, 21.4%), and cerebral microhemorrhage (13.8%, 19.6%). Plasma ponezumab increased dose‐dependently with limited accumulation. Cerebrospinal fluid penetration was low. Plasma Aβ 1–x and Aβ 1–40 showed robust increases, but cerebrospinal fluid biomarkers showed no dose response. Ponezumab had no effects on cognitive/functional outcomes or brain volume. Conclusions Multiple‐dose ponezumab was generally safe, but not efficacious, in mild‐to‐moderate AD.

Abstract The Division of Lung Diseases of the NHLBI and the Cardiovascular Medical Education and Research Fund held a workshop to discuss how to leverage the anticipated scientific output from the recently launched “Redefining Pulmonary Hypertension through Pulmonary Vascular Disease Phenomics” (PVDOMICS) program to develop newer approaches to pulmonary vascular disease. PVDOMICS is a collaborative, protocol-driven network to analyze all patient populations with pulmonary hypertension to define novel pulmonary vascular disease (PVD) phenotypes. Stakeholders, including basic, translational, and clinical investigators; clinicians; patient advocacy organizations; regulatory agencies; and pharmaceutical industry experts, joined to discuss the application of precision medicine to PVD clinical trials. Recommendations were generated for discussion of research priorities in line with NHLBI Strategic Vision Goals that include: (1) A national effort, involving all the stakeholders, should seek to coordinate biosamples and biodata from all funded programs to a web-based repository so that information can be shared and correlated with other research projects. Example programs sponsored by NHLBI include PVDOMICS, Pulmonary Hypertension Breakthrough Initiative, the National Biological Sample and Data Repository for PAH, and the National Precision Medicine Initiative. (2) A task force to develop a master clinical trials protocol for PVD to apply precision medicine principles to future clinical trials. Specific features include: (a) adoption of smaller clinical trials that incorporate biomarker-guided enrichment strategies, using adaptive and innovative statistical designs; and (b) development of newer endpoints that reflect well-defined and clinically meaningful changes. (3) Development of updated and systematic variables in imaging, hemodynamic, cellular, genomic, and metabolic tests that will help precisely identify individual and shared features of PVD and serve as the basis of novel phenotypes for therapeutic interventions.

10 Background: Our objective was to evaluate the cost-utility of 3 lymphadenectomy (LND) strategies in the treatment of low-risk endometrial cancer (EC). Methods: A decision analysis model compared 3 LND strategies in women undergoing minimally invasive surgery (MIS) for EC: 1) routine LND in all pts; 2) selective LND based on intraoperative frozen section, in which 60% of pts undergo LND; and 3) sentinel lymph node mapping (SLN) based on a published algorithm, in which 15% of pts map unilaterally (requiring a contralateral LND) and 5% don’t map (requiring bilateral LND). Costs and outcomes were obtained from published literature and Medicare reimbursement rates. Costs categories consisted of hospital, physician, operating room, pathology, and lymphedema treatment. Effectiveness was defined as 3-year disease-specific survival adjusted for the impact of lymphedema (utility = 0.8) on quality of life. Incremental cost-effectiveness ratios (ICERs) per quality-adjusted life years (QALYs) gained were calculated. QALYs and costs were discounted at an annual 3% rate. Results: For the estimated 40,000 women undergoing surgery for low-risk EC each year in the US, the annual cost of routine LND, selective LND, and SLN is $722 million, $681 million, and $656 million respectively. In the base case scenario, routine LND had a cost of $18,041 and an effectiveness of 2.79 QALYs. Selective LND had a cost of $17,036 and an effectiveness of 2.81 QALYs, while SLN had a cost of $16,401 and an effectiveness of 2.87 QALYs. With a difference of $1,005 and 0.02 QALYs, selective LND was both less costly and more effective than routine LND, dominating it. However, with the lowest cost and highest effectiveness, SLN dominated the other modalities and was the most cost-effective strategy. No ICER could be determined. These findings were robust to multiple one- and two-way sensitivity analyses varying the rates of lymphedema and LND, surgical approach (open or MIS), lymphedema utility, and costs. Conclusions: Compared to routine and selective LND, SLN had the lowest cost and highest quality-adjusted survival, making it the most cost-effective strategy in the management of low-risk EC.

Abstract Purpose: We aimed to establish the MTD of the poly (ADP-ribose) (PAR) polymerase inhibitor, veliparib, in combination with carboplatin in germline BRCA1- and BRCA2- (BRCA)-associated metastatic breast cancer (MBC), to assess the efficacy of single-agent veliparib, and of the combination treatment after progression, and to correlate PAR levels with clinical outcome. Experimental Design: Phase I patients received carboplatin (AUC of 5–6, every 21 days), with escalating doses (50-20 mg) of oral twice-daily (BID) veliparib. In a companion phase II trial, patients received single-agent veliparib (400 mg BID), and upon progression, received the combination at MTD. Peripheral blood mononuclear cell PAR and serum veliparib levels were assessed and correlated with outcome. Results: Twenty-seven phase I trial patients were evaluable. Dose-limiting toxicities were nausea, dehydration, and thrombocytopenia [MTD: veliparib 150 mg po BID and carboplatin (AUC of 5)]. Response rate (RR) was 56%; 3 patients remain in complete response (CR) beyond 3 years. Progression-free survival (PFS) and overall survival (OS) were 8.7 and 18.8 months. The PFS and OS were 5.2 and 14.5 months in the 44 patients in the phase II trial, with a 14% RR in BRCA1 (n = 22) and 36% in BRCA2 (n = 22). One of 30 patients responded to the combination therapy after progression on veliparib. Higher baseline PAR was associated with clinical benefit. Conclusions: Safety and efficacy are encouraging with veliparib alone and in combination with carboplatin in BRCA-associated MBC. Lasting CRs were observed when the combination was administered first in the phase I trial. Further investigation of PAR level association with clinical outcomes is warranted. Clin Cancer Res; 23(15); 4066–76. ©2017 AACR.

Background and purpose Because computed tomography (CT) is the most commonly used imaging modality for the evaluation of acute ischemic stroke patients, developing CT-based techniques for improving clot characterization could prove useful. The purpose of this in-vitro study was to determine which single-energy or dual-energy CT techniques provided optimum discrimination between red blood cell (RBC) and fibrin-rich clots. Materials and methods Seven clot types with varying fibrin and RBC densities were made (90% RBC, 99% RBC, 63% RBC, 36% RBC, 18% RBC and 0% RBC with high and low fibrin density) and their composition was verified histologically. Ten of each clot type were created and scanned with a second generation dual source scanner using three single (80 kV, 100 kV, 120 kV) and two dual-energy protocols (80/Sn 140 kV and 100/Sn 140 kV). A region of interest (ROI) was placed over each clot and mean attenuation was measured. Receiver operating characteristic curves were calculated at each energy level to determine the accuracy at differentiating RBC-rich clots from fibrin-rich clots. Results Clot attenuation increased with RBC content at all energy levels. Single-energy at 80 kV and 120 kV and dual-energy 80/Sn 140 kV protocols allowed for distinguishing between all clot types, with the exception of 36% RBC and 18% RBC. On receiver operating characteristic curve analysis, the 80/Sn 140 kV dual-energy protocol had the highest area under the curve for distinguishing between fibrin-rich and RBC-rich clots (area under the curve 0.99). Conclusions Dual-energy CT with 80/Sn 140 kV had the highest accuracy for differentiating RBC-rich and fibrin-rich in-vitro thrombi. Further studies are needed to study the utility of non-contrast dual-energy CT in thrombus characterization in acute ischemic stroke.