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Anthony L. Asher, Matthew J. McGirt and Zoher Ghogawala

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Anthony L. Asher, Paul C. McCormick and Douglas Kondziolka

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Walter A. Hall, Edward Rustamzadeh and Anthony L. Asher

The poor prognosis associated with the current management of malignant gliomas has led investigators to develop alternative treatments such as targeted toxin therapy. The optimal method for administering these agents is under development but appears to be convection-enhanced delivery (CED).

The direct intratumoral infusion of targeted toxins was first performed in nude mouse flank tumor models of human malignant glioma. After the demonstration of in vivo efficacy, these potent cytotoxic compounds were tested in Phase I and Phase II clinical trials.

Using a high-flow microinfusion technique, volumes of up to 180 ml were infused by CED through catheters placed directly into brain tumors. Minor systemic toxicity was seen in the form of hepatic enzyme elevation. Neural toxicity manifested as seizure activity and hemiparesis resulted from peritumoral edema that followed the completion of the infusion. Peritumoral toxicity was believed to be more related to the concentration of the infused immunotoxin than to the infusion volume. In approximately half of patients treated with CED a stable disease course, a partial response, or a complete response was demonstrated in some clinical trials.

Targeted toxin therapy has clinical efficacy in patients with malignant gliomas. Convection-enhanced delivery appears to represent an effective method for administering these agents in patients with malignant brain tumors.

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Anthony L. Asher, Paul C. McCormick, Nathan R. Selden, Zoher Ghogawala and Matthew J. McGirt

Patient care data will soon inform all areas of health care decision making and will define clinical performance. Organized neurosurgery believes that prospective, systematic tracking of practice patterns and patient outcomes will allow neurosurgeons to improve the quality and efficiency and, ultimately, the value of care. In support of this mission, the American Association of Neurological Surgeons, in cooperation with a broad coalition of other neurosurgical societies including the Congress of Neurological Surgeons, Society of Neurological Surgeons, and American Board of Neurological Surgery, created the NeuroPoint Alliance (NPA), a not-for-profit corporation, in 2008. The NPA coordinates a variety of national projects involving the acquisition, analysis, and reporting of clinical data from neurosurgical practice using online technologies. It was designed to meet the health care quality and related research needs of individual neurosurgeons and neurosurgical practices, national organizations, health care plans, biomedical industry, and government agencies. To meet the growing need for tools to measure and promote high-quality care, NPA collaborated with several national stakeholders to create an unprecedented program: the National Neurosurgery Quality and Outcomes Database (N2QOD). This resource will allow any US neurosurgeon, practice group, or hospital system to contribute to and access aggregate quality and outcomes data through a centralized, nationally coordinated clinical registry. This paper describes the practical and scientific justifications for a national neurosurgical registry; the conceptualization, design, development, and implementation of the N2QOD; and the likely role of prospective, cooperative clinical data collection systems in evolving systems of neurosurgical training, continuing education, research, public reporting, and maintenance of certification.

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Matthew J. McGirt, Theodore Speroff, Robert S. Dittus, Frank E. Harrell Jr. and Anthony L. Asher

Given the unsustainable costs of US health care, universal agreement exists among payers, regulatory agencies, and other health care stakeholders that reform must include substantial improvements in the quality, effectiveness, and value of health care delivery. The Institute of Medicine and the American Recovery and Reinvestment Act of 2009 have called for the establishment of prospective registries to capture patient-centered data from real-world practice as a high priority to guide evidence-based reform. As a result, the American Association of Neurological Surgeons launched the National Neurosurgery Quality and Outcomes Database (N2QOD) and began enrolling patients in March 2012 into its initial pilot project: a web-based lumbar spine module. As a nationwide, prospective longitudinal registry utilizing patient reported outcome instruments, the N2QOD lumbar spine surgery pilot aims to systematically measure and aggregate surgical safety and 1-year postoperative outcome data from approximately 30 neurosurgical practices across the US with the primary aim of demonstrating the feasibility and validity of standardized 1-year outcome measurement from everyday real-world practice. At the end of the pilot year, 1) risk-adjusted modeling will be developed for the safety, quality, and effectiveness of lumbar surgical care (morbidity, readmission, improvements in pain, disability, quality of life, and return to work); 2) data integrity and validation will be demonstrated via internal quality control analyses and auditing, and 3) the feasibility of obtaining a high level of follow-up (~80%) of nationwide 1-year outcome measurement will be established. N2QOD will use only prospective clinical data, will avoid the use of administrative data proxies, and will rely on neurosurgically relevant risk factors for risk adjustment. Once national benchmarks of quality and effectiveness are accurately established and validated utilizing practice-based data extractors in the pilot year, N2QOD aims to introduce non–full-time employee (FTE)–dependent methodologies such as electronic medical record auto-extraction. N2QOD's non–FTE-dependent methodologies can then be validated against practice-based data extractor–derived measures of safety and effectiveness with the aim of more rapid expansion into the majority of US practice groups. The general overview, methods, and registry design of the N2QOD pilot year (lumbar module) are presented here.

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Matthew J. McGirt, Ahilan Sivaganesan, Anthony L. Asher and Clinton J. Devin

OBJECT

Lumbar spine surgery has been demonstrated to be efficacious for many degenerative spine conditions. However, there is wide variability in outcome after spine surgery at the individual patient level. All stakeholders in spine care will benefit from identification of the unique patient or disease subgroups that are least likely to benefit from surgery, are prone to costly complications, and have increased health care utilization. There remains a large demand for individual patient-level predictive analytics to guide decision support to optimize outcomes at the patient and population levels.

METHODS

One thousand eight hundred three consecutive patients undergoing spine surgery for various degenerative lumbar diagnoses were prospectively enrolled and followed for 1 year. A comprehensive patient interview and health assessment was performed at baseline and at 3 and 12 months after surgery. All predictive covariates were selected a priori. Eighty percent of the sample was randomly selected for model development, and 20% for model validation. Linear regression was performed with Bayesian model averaging to model 12-month ODI (Oswestry Disability Index). Logistic regression with Bayesian model averaging was used to model likelihood of complications, 30-day readmission, need for inpatient rehabilitation, and return to work. Goodness-of-fit was assessed via R2 for 12-month ODI and via the c-statistic, area under the receiver operating characteristic curve (AUC), for the categorical endpoints. Discrimination (predictive performance) was assessed, using R2 for the ODI model and the c-statistic for the categorical endpoint models. Calibration was assessed using a plot of predicted versus observed values for the ODI model and the Hosmer-Lemeshow test for the categorical endpoint models.

RESULTS

On average, all patient-reported outcomes (PROs) were improved after surgery (ODI baseline vs 12 month: 50.4 vs 29.5%, p < 0.001). Complications occurred in 121 patients (6.6%), 108 (5.9%) were readmitted within 30 days of surgery, 188 (10.3%) required discharge to inpatient rehabilitation, 1630 (88.9%) returned to work, and 449 (24.5%) experienced an unplanned outcome (no improvement in ODI, a complication, or readmission). There were 45 unique baseline variable inputs, derived from 39 clinical variables and 38 questionnaire items (ODI, SF-12, MSPQ, VAS-BP, VAS-LP, VAS-NP), included in each model. For prediction of 12-month ODI, R2 was 0.51 for development and 0.47 for the validation study. For prediction of a complication, readmission, inpatient rehabilitation, and return to work, AUC values ranged 0.72-0.84 for development and 0.79-0.84 for validation study.

CONCLUSIONS

A novel prediction model utilizing both clinical data and patient interview inputs explained the majority of variation in outcome observed after lumbar spine surgery and reliably predicted 12-month improvement in physical disability, return to work, major complications, readmission, and need for inpatient rehabilitation for individual patients. Application of these models may allow clinicians to offer spine surgery specifically to those who are most likely to benefit and least likely to incur complications and excess costs.

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Scott L. Parker, Anthony L. Asher, Saniya S. Godil, Clinton J. Devin and Matthew J. McGirt

OBJECT

The health care landscape is rapidly shifting to incentivize quality of care rather than quantity of care. Quality and outcomes registry platforms lie at the center of all emerging evidence-driven reform models and will be used to inform decision makers in health care delivery. Obtaining real-world registry outcomes data from patients 12 months after spine surgery remains a challenge. The authors set out to determine whether 3-month patient-reported outcomes accurately predict 12-month outcomes and, hence, whether 3-month measurement systems suffice to identify effective versus noneffective spine care.

METHODS

All patients undergoing lumbar spine surgery for degenerative disease at a single medical institution over a 2-year period were enrolled in a prospective longitudinal registry. Patient-reported outcome instruments (numeric rating scale [NRS], Oswestry Disability Index [ODI], 12-Item Short Form Health Survey [SF-12], EQ-5D, and the Zung Self-Rating Depression Scale) were recorded prospectively at baseline and at 3 months and 12 months after surgery. Linear regression was performed to determine the independent association of 3- and 12-month outcome. Receiver operating characteristic (ROC) curve analysis was performed to determine whether improvement in general health state (EQ-5D) and disability (ODI) at 3 months accurately predicted improvement and achievement of minimum clinical important difference (MCID) at 12 months.

RESULTS

A total of 593 patients undergoing elective lumbar surgery were included in the study. There was a significant correlation between 3-month and 12-month EQ-5D (r = 0.71; p < 0.0001) and ODI (r = 0.70; p < 0.0001); however, the authors observed a sizable discrepancy in achievement of a clinically significant improvement (MCID) threshold at 3 versus 12 months on an individual patient level. For postoperative disability (ODI), 11.5% of patients who achieved an MCID threshold at 3 months dropped below this threshold at 12 months; 10.5% of patients who did not meet the MCID threshold at 3 months continued to improve and ultimately surpassed the MCID threshold at 12 months. For ODI, achieving MCID at 3 months accurately predicted 12-month MCID with only 62.6% specificity and 86.8% sensitivity. For postoperative health utility (EQ-5D), 8.5% of patients lost an MCID threshold improvement from 3 months to 12 months, while 4.0% gained the MCID threshold between 3 and 12 months postoperatively. For EQ-5D (quality-adjusted life years), achieving MCID at 3 months accurately predicted 12-month MCID with only 87.7% specificity and 87.2% sensitivity.

CONCLUSIONS

In a prospective registry, patient-reported measures of treatment effectiveness obtained at 3 months correlated with 12-month measures overall in aggregate, but did not reliably predict 12-month outcome at the patient level. Many patients who do not benefit from surgery by 3 months do so by 12 months, and, conversely, many patients reporting meaningful improvement by 3 months report loss of benefit at 12 months. Prospective longitudinal spine outcomes registries need to span at least 12 months to identify effective versus noneffective patient care.

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Richard P. Menger, Bharat Guthikonda, Christopher M. Storey, Anil Nanda, Matthew McGirt and Anthony Asher

Neurosurgeons provide direct individualized care to patients. However, the majority of regulations affecting the relative value of patient-related care are drafted by policy experts whose focus is typically system- and population-based. A central, prospectively gathered, national outcomes-related database serves as neurosurgery’s best opportunity to bring patient-centered outcomes to the policy arena.

In this study the authors analyze the impact of the Affordable Care Act (ACA) on the determination of quality and value in neurosurgery care through the scope, language, and terminology of policy experts. The methods by which the ACA came into law and the subsequent quality implications this legislation has for neurosurgery will be discussed. The necessity of neurosurgical patient-oriented clinical registries will be discussed in the context of imminent and dramatic reforms related to medical cost containment.

In the policy debate moving forward, the strength of neurosurgery’s argument will rest on data, unity, and proactiveness. The National Neurosurgery Quality and Outcomes Database (N2QOD) allows neurosurgeons to generate objective data on specialty-specific value and quality determinations; it allows neurosurgeons to bring the patient-physician interaction to the policy debate.