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SPINE Volume 40, Number 14, pp 1072-1078 ©2015, Wolters Kluwer Health, Inc. All rights reserved.

CERVICAL SPINE

A Novel Quality-of-Life Utility Index in Patients With Multilevel Cervical Degenerative Disc Disease Comparison of Anterior Cervical Discectomy and Fusion With Total Disc Replacement Jared D. Ament, MD, MPH,* Zhuo Yang, PhD,* Yingjia Chen, PhD,* Ross S. Green, BS,† and Kee D. Kim, MD*

Study Design. Decision analysis from prior randomized controlled trial (RCT) data. Objective. To describe the importance of developing baseline utility indices while identifying effective treatment options for cervical spine disease. Summary of Background Data. Cervical total disc replacement (CTDR) was developed to treat cervical spondylosis while preserving motion. Although anterior cervical discectomy and fusion (ACDF) has been the standard of care, a recent RCT suggested similar outcomes for 2-level disease. The quality-of-life benefit afforded by both CTDR and ACDF has never been fully elucidated. The purpose of our investigation was to better define the changes in utility and perceived value for patients undergoing these procedures. Methods. Data were derived from LDR’s RCT comparing CTDR and ACDF for 2-level cervical disc disease. Using linear regression, we constructed health states on the basis of the stratification of clinical outcomes used in the RCT, namely, neck disability index and visual analogue scale. Data from SF-12 questionnaires, completed preoperatively and at each follow-up visit, were transformed into utilities using the SF-6D mapping algorithm. SAS v.9.3 was used for the analyses. Results. A strong correlation (R2= 0.6864, P < 0.0001) was found between neck disability index and visual analogue scale. We constructed 5 distinct health states by projecting neck disability index intervals onto visual analogue scale. A poorer health state was

From the *University of California Davis, Sacramento, CA; and †Ben-Gurion University, Beer-Sheva, Israel. Acknowledgment date: October 5, 2014. Revision date: February 3, 2015. Acceptance date: March 17, 2015. The device(s)/drug(s) is/are FDA approved or approved by corresponding national agency for this indication. Consulting funds were received in support of this work. Relevant financial activities outside the submitted work: consultancy, board membership, grant/grants pending, patents, payment for lectures, royalties, stock. Address correspondence and reprint requests to Jared D. Ament, MD, MPH, Department of Neurological Surgery, University of California Davis, 4860 Y St, #3740, Sacramento, CA 95817; E-mail: jared.ament@ucdmc.ucdavis.edu DOI: 10.1097/BRS.0000000000000898

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associated with a lower mean utility value whereas a higher health state was associated with a higher mean utility value (P < 0.0001). The difference in preoperative utility between 2-level ACDF and CTDR was not significant (P = 0.1982), and yet, the difference in the postoperative utility between the cohorts was significant (P < 0.05) at every time point collected from 6 to 60 months. Conclusion. This is the first instance in which distinct utility values have been derived for validated health states related to cervical spine disease. There is substantial potential for these to become baseline future indices for cost-utility analyses in similar populations. Key words: utility analysis, Mobi-C, artificial disc, cervical spondylosis, total disc replacement, spine fusion, decision analysis. Level of Evidence: 1 Spine 2015;40:1072–1078

A

nterior cervical discectomy and fusion (ACDF) and cervical total disc replacement (CTDR) were both developed to treat neck pain and neurological sequelae associated with cervical spondylosis. The latter has been proposed to improve quality of life (QOL) while preserving motion, and several CTDR devices have moved beyond the investigational stage and been approved for use. Several large-scale Food and Drug Administration–regulated Investigational Device Exemption clinical trials have demonstrated noninferiority for single-level disease. Despite this, QOL differences have been more challenging to demonstrate. In the past, this has been due to a lack of data because QOL information cannot be accurately collected retrospectively because of the enormous influence of recall bias. Both the Standard Gamble and Time Trade Off methods were originally described1 but found to be challenging because our risk adverse nature results in our underestimating of our health status.1–3 Preference-based QOL instruments, such as SF-36 and SF-12, are now commonplace in health care studies as well as validated algorithms that enable conversion of the result into utility values (the accepted health state index). As a result, the practice of comparing utility values across interventions is now prevalent in the literature. This is

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CERVICAL SPINE further precipitated by the fact that our allocation of medical resources has never been more scrutinized than it is currently. Recently, Qureshi et al4 published utility values for both ACDF and CTDR groups, pre- and postoperatively, for singlelevel degenerative disc disease (DDD). They showed a significant improvement in QOL (increased utility) in both groups when compared with their preoperative state (0.54), with no difference between the 2 groups (0.71 for ACDF and 0.72 for CTDR at 24 mo, P = 0.5989). Multilevel DDD is more common in our increasingly more active and aging population.5 Whether pre- and postsurgical QOL in the multilevel DDD population is similar to the single-level cohort is unknown. This study aims to determine the baseline level of health (utility) in patients with 2-level cervical DDD as well as their QOL after surgical intervention with either ACDF or CTDR.

MATERIALS AND METHODS Data Source Data were derived from a published randomized controlled trial (RCT)6 comparing CTDR (US Food and Drug Administration Investigational Device Exemption trial for Mobi-C) with ACDF for 2-level DDD. Patients included in the trial (n = 331) had to be diagnosed with radiculopathy or myeloradiculopathy at 2 contiguous levels from C3 to C7 who were unresponsive to conservative treatment for at least 6 weeks or demonstrated progressive symptoms. The specific methodology from the RCT is not included here for brevity. All statistical analyses were conducted using SAS v.9.3. All modeling works were done using TreeAge Pro R1.1.

Utility Score Calculation The QOL of each patient was evaluated for 60 months postoperatively, with SF-127 data collected preoperatively and at 6 weeks and 3, 6, 12, 24, 36, 48, and 60 months. Two methods exist for converting SF-12 data into single utility values on a scale from 0 to 1. The first and most commonly used algorithm is the EQ-5D index score. The second method uses aspects of the SF-12 to compose the SF-6D index score. This index has been shown to correlate with US preference–based utility measurements.8 The latter was used here because of an acknowledged ceiling effect intrinsic to the EQ-5D mapping algorithm at low-utility levels (mild medical problems, slight depression, minimal disability).9 The SAS-based mapping algorithm used to convert SF-12 to SF-6D was obtained from The University of Sheffield.10 SF-6D index scores were used as the measure of health utility. Mean utility and standard deviations were computed for each of the 5 health states. Pre- and postoperative health states, with the associated utility value, were then determined for each of the surgical cohorts. All data were analyzed using SAS v.9.3 and TreeAge Pro R1.1.

Neck Disability Index and Visual Analogue Scale– Based Health States We initially defined health states by stratifying clinical outcome measurements used in the RCT. The 2 major quantitative Spine

Quality of Life Utility Index • Ament et al

measurements used were neck disability index (NDI) and visual analogue scale (VAS) for neck and arm pain. Because NDI has an established interpretation for each score interval (see Supplemental Digital Content Appendix A1, available at: http://links.lww.com/BRS/A978),11 it was chosen as our independent variable to calculate estimated VAS in a univariate regression model. The NDI interval and the estimated VAS interval were then used to construct the corresponding health states. The health states constructed are, in an ascending order of severity, minimal disability (NDI ≤20 and VAS ≤21), moderate disability (21 ≤ NDI ≤ 40 and 22 ≤ VAS ≤ 44), severe disability (41 ≤ NDI ≤ 60 and 45 ≤ VAS ≤ 67), crippled (61 ≤ NDI ≤ 80 and 68 ≤ VAS ≤ 90), and bedbound (81 ≤ NDI ≤ 100 and 91 ≤ VAS ≤ 100). We then used the NDI and VAS score collected preoperatively and at 6 weeks and 3, 6, 12, 24, 36, 48, and 60 months to identify the patient’s health state at each follow-up interval. We pooled all the SF-6D-based utility values associated with a particular health state, irrespective of the time of collection or surgery type, to calculate the health state–specific utility score.

Markov Model for Postsurgical Recovery Using the constructed health states, we were able to quantitatively examine how patients’ health changed over time since surgical intervention. We created a Markov model to achieve this and determine transition probabilities between health states. It is a common practice that transition probabilities in a cohort Markov model are set at fixed intervals. For example, cancer recurrence rate would be set equal to various times points postoperatively. This practice is problematic in our setting because recovery is not linear in this patient population. The cohort experiences rapid symptomatic improvement postoperatively; this recovery pace, however, then slows over time. The transition probabilities must capture this feature of decelerating recovery. Therefore, we divided follow-up time (from surgery to 60 mo postoperatively) into 5 segments: 0 to 6 weeks, 6 weeks to 6 months, 6 months to 1 year, 1 year to 2 years, and 2 years to 5 years. Transition probabilities are independently calculated for each segment. Before calculating segment-specific transition probabilities, we used imputation for missing health states when encountered in the data set. We assumed a gradual recovery in instances of consecutively missing health states. For example, if a patient had a health state of 4 at 12 months and 1 at 48 months and was missing data for the 24- and 36-month intervals, then health states of 3 and 2 were imputed, respectively. Health states were not imputed when patients were lost to follow-up. We also used the Markov model to determine patients’ cumulative time spent in each health state over the 60-month follow-up period.

RESULTS There was no statistical difference between the CTDR and ACDF cohorts with regard to age, sex, ethnicity, body mass index, smoking history, preoperative narcotic use, working www.spinejournal.com

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CERVICAL SPINE status, driving status, or use of ancillary services, such as physical therapy and cervical traction.6 In the CTDR group, 193 (58.3%) patients had at least 60 months of follow-up. In the ACDF group, 84 patients (25.4%) had at least 60 months of follow-up. Looking at 5-year follow-up data, we projected VAS (dependent variable) onto NDI scores (independent variable) using linear regression resulting in unique health states (Figure 1). A strong correlation between VAS and NDI was identified, R2= 0.6858. From this regression, 5 distinct health states were created. Health state 1 represented the minimally disabled whereas health state 5 referred to the bedbound patient (Figure 1). The distribution of each surgical cohort in particular health states at each point in time is shown in Figure 2. Both groups demonstrate an overall transition from worse to improved health states over time. The average number of months a patient spent in each health state is depicted in Table 1. For example, at 60 months, the ACDF patient spent an average of 3.7 months (6%) in the bedbound state compared with 0.9 out of 60 follow-up months (2%) for the CTDR patient. Similarly, the ACDF patient spent an average of 25.1 out of 60 follow-up months (42% of the time) in the minimal disability health state compared with 35.5 months (59%) for the CTDR group. The SF-12 results were transformed into SF-6D utility scores. The distribution of pre- and postsurgical utility scores is seen in Figure 3. A clear trend toward improved utility (QOL) is appreciated for both surgical cohorts. There was a statistically significant change in mean utility (0.203) when comparing the entire cohort of patients pre- and postoperatively at 60 months (P < 0.002). Preoperative mean utility in the ACDF group increased from 0.545 to 0.711 postoperatively at 60 months. Utility similarly increased in the CTDR group from 0.556 preoperatively to 0.776 postoperatively at 60 months. The difference in preoperative utility between the 2-level ACDF and 2-level CTDR was not significant (P = 0.198), and yet the difference in the postoperative utility

Figure 1. NDI and VAS-based stratification of health states. NDI indicates neck disability index; VAS, visual analogue scale.

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between the 2 surgical cohorts was significant (P < 0.05) at every time point collected from 6 to 60 months (Table 2). Mean utility values were assigned to each derived health state and a clear correlation was found (Table 3). A poorer health state was associated with a lower mean utility value and a higher health state was associated with a higher mean utility value. These differences in mean utility at each health state were statistically significant by analysis of variance calculations (ANOVA, P < 0.001).

DISCUSSION In the Mobi-C Investigational Device Exemption study, CTDR demonstrated superiority over ACDF for 2-level DDD at 2 years. ACDF and CTDR are 2 possible surgical options for treatment of DDD. During the past decade, a growing body of level 1 evidence has demonstrated the potential of CTDR as an alternative to ACDF, with studies focusing almost entirely on single-level treatments.12,13 These studies have almost exclusively concluded noninferiority of CTDR to ACDF. In practice, however, patients often experience multilevel pathology. The data analyzed from this study demonstrated overall success rates of 69.7% and 37.4% for the CTDR and ACDF groups, respectively, which met the noninferiority margin and established statistical superiority of CTDR over ACDF for 2-level DDD.6 This finding agrees with studies that have compared single-level and multilevel CTDR and found similar success rates.14,15 To our knowledge, this is the first study in which distinct health states with associated QOL utility indices have been derived for multilevel cervical DDD with 60 months of follow-up. Utility-associated health states allow for quantitative categorization and longitudinal assessment of patients’ QOL. When the allocation of limited health care resource is being heavily scrutinized, this type of metric can help inform reimbursement and clinical decision making. There is also potential for these validated health states to become baseline indices for future cost-utility analyses in similar populations. Using the data from LDR’s Mobi-C multicenter RCT,6 most patients with multilevel DDD had a preoperative utility value of approximately 0.55, placing them in the crippled health state. There was no statistically significant difference in this preoperative health state between the 2 surgical groups (P = 0.198). A notable improvement in health state category was observed in both groups at the initial 6-week follow-up visit (Figure 2). This trend continued as follow-up duration increased, with patients from both surgical groups improving to better health states, suggesting an improved QOL. At 12 months, ACDF and CTDR patients spent 34% and 45% of their postoperative time in the minimal disability health state compared with 42% and 59% at 60 months, respectively (Table 1). Transition probabilities from our Markov model illustrate this trend in more detail and can be found in the Supplemental Digital Content Appendix (A2 and A3), available at: http://links.lww.com/BRS/A979 and http://links.lww. com/BRS/A980. Despite the overall trend toward improvement in both surgical groups, by 6 months postoperatively,

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CERVICAL SPINE

Quality of Life Utility Index • Ament et al

100%

80%

60%

40%

20%

0%

100%

1 yr 80%

60%

40%

20%

0%

100%

6 mo 80%

60%

40%

20%

0%

100%

80%

3 mo 60%

40%

20%

0%

6 wk 100%

80%

60%

40%

20%

0%

before surgery

Minimal disability Moderate disability Severe disability Crippled Bedbound

18 mo

2 yr

3 yr

4 yr

5 yr

Minimal disability Moderate disability Severe disability Crippled Bedbound

ACDF

CTDR

Figure 2. Pre- and postsurgical distribution of neck disability index and visual analogue scale–based health states. ACDF indicates anterior cervical discectomy and fusion; CTDR, cervical total disc replacement.

the CTDR cohort demonstrated significant differences in mean utility scores at each follow-up period (Table 2). Comparatively, patients with single-level cervical DDD were also found to start, on average, in the crippled health state, with utility scores of 0.54.4 Postoperatively at 2 years,

TABLE 1. Average Number of Months in Each

Health State, Since Index Surgery 1 yr

2 yr

5 yr

Month (%)

Month (%)

Month (%)

ACDF

4.1 (34)

9.3 (39)

25.1 (42)

CTDR

5.4 (45)

12.8 (53)

35.5 (59)

ACDF

2.5 (21)

4.9 (20)

13.0 (22)

CTDR

2.8 (23)

4.9 (21)

11.9 (20)

ACDF

0.9 (8)

1.6 (7)

3.7 (6)

CTDR

0.2 (2)

0.4 (2)

0.9 (2)

ACDF

1.9 (16)

3.2 (13)

6.6 (11)

CTDR

1.5 (13)

2.4 (10)

4.8 (8)

ACDF

2.6 (22)

5.0 (21)

11.6 (19)

CTDR

2.1 (17)

3.5 (14)

6.9 (12)

Minimal disability

Moderate disability

Bedbound disability

Crippled disability

Severe disability

ACDF indicates anterior cervical discectomy and fusion; CTDR, cervical total disc replacement.

Spine

ACDF patients attained health states (0.71) similar to our 2-level ACDF patients at 5 years (0.71), corresponding to the moderate disability health state. QOL seemed to improve slightly more in our 2-level CTDR group at 5 years (0.78) than in single-level CTDR at 2 years (0.72). For reference, patients with no light perception visual acuity have an understandably poor QOL and have been found to have utility scores of 0.29 (Table 4).16 Patients after minor strokes enter health states similar to our postoperative ACDF patients with utility values of 0.71,17 and, interestingly, postoperative lumber discectomy patients, on average, enjoy a high QOL with utility scores of 0.84.18 Although our analysis seems consistent with previous studies that addressed health states and QOL for single-level cervical DDD, the data are limited by its reliance on a single multicenter RCT focusing on 1 type of CTDR. This may limit the generalizability of our derived health states. The disparity in available follow-up data at 60 months between the surgical groups (58.3% in CTDR vs. 25.4% in ACDF) may also influence the final utility calculations, although it is impossible to determine the direction of the bias, if any exists. The authors do think that any bias is mitigated, however, because the analysis was inherently dependent on both ACDF and CTDR cohorts, which was not statistically significant preoperatively. This also represents a QOL analysis with the longest outcome and follow-up data available for comparing ACDF and CTDR in multilevel cervical DDD. Furthermore, the authors suggest that a QOL analysis for 2-level pathology is more realistic because much of our older patient population has multilevel disease. Unlike other fields, such as ophthalmology with visual acuity measurements and other validated utility transformations, spine surgery lacks metrics that are easily correlated with QOL. In an era of cost-effective medicine and health care reform, there is significant value in identifying these www.spinejournal.com

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Quality of Life Utility Index • Ament et al

Before surgery Percentage

40%

6 mo

ACDF n=104 CTDR n=227

40%

50%

ACDF n=95 CTDR n=212

40%

30%

30%

30%

20%

20%

20%

10%

10%

10%

24 mo

18 mo 50% 40%

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

ACDF n=90 CTDR n=214

0%

0%

0%

Percentage

12 mo

50%

50%

36 mo 50%

50%

ACDF n=90 CTDR n=208

40%

ACDF n=97 CTDR n=219

40%

30%

30%

30%

20%

20%

20%

10%

10%

10%

0%

0%

0% 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

ACDF n=82 CTDR n=201

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Ulity Score

48 mo

60 mo

Percentage

50% 40%

50%

ACDF n=76 CTDR n=193

40%

30%

30%

20%

20%

10%

10%

0%

ACDF n=84 CTDR n=193

ACDF CTDR

0% 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Ulity Score

Ulity Score

Figure 3. Distribution of pre- and postsurgical utility score by surgery type. ACDF indicates anterior cervical discectomy and fusion; CTDR, cervical total disc replacement.

TABLE 2. Pre and Postsurgery Utility Score Presurgery

6 mo

12 mo

18 mo

24 mo

36 mo

48 mo

60 mo

331

307

304

298

316

283

269

277

0.553 (0.112)

0.752 (0.162)

0.753 (0.169)

0.751 (0.168)

0.761 (0.159)

0.762 (0.173)

0.762 (0.164)

0.756 (0.157)

104

95

90

90

97

82

76

84

0.545 (0.111)

0.720 (0.171)

0.722 (0.176)

0.718 (0.183)

0.719 (0.166)

0.716 (0.184)

0.722 (0.177)

0.711 (0.173)

227

212

214

208

219

201

193

193

0.556 (0.113)

0.767 (0.156)

0.766 (0.164)

0.765 (0.160)

0.779 (0.153)

0.781 (0.150)

0.777 (0.156)

0.776 (0.145)

0.1982

0.0183

0.0381

0.0262

0.0020

0.0024

0.0129

0.0017

Total n Mean utility (SE) ACDF n Mean utility (SE) CTDR n Mean utility (SE) P* (∆utility)

*P value here is based on the 1-tail t test of null hypothesis that the utility improvement of patients receiving CTDR at certain postsurgery time point compared with presurgical status is not higher than that of those receiving ACDF at the same time point. ACDF indicates anterior cervical discectomy and fusion; CTDR, cervical total disc replacement.

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CERVICAL SPINE

Quality of Life Utility Index • Ament et al

TABLE 3. Utility Value for NDI and VAS-Based Health States Disability Score Range

Mean

SD

Minimal disability

NDI ≤20 and VAS ≤21

0.849

0.117

Moderate disability

21 ≤ NDI ≤ 40 and 22 ≤ VAS ≤ 44

0.689

0.117

Severe disability

41 ≤ NDI ≤ 60 and 45 ≤ VAS ≤ 67

0.609

0.111

Crippled

61 ≤ NDI ≤ 80 and 68 ≤ VAS ≤ 90

0.548

0.099

81 ≤ NDI ≤ 100 and 91 ≤ VAS ≤ 100

0.478

0.100

Bedbound

NDI indicates neck disability index; VAS, visual analogue scale.

relationships. The authors hope that this work will enable future researchers to follow patients with multilevel cervical DDD in a clear and systematic manner. Utility indices are a novel method to track and assess changes in QOL and patient health states. This may facilitate additional QOL calculations (i.e., utility change, disutility, QALY [quality adjusted life year], ICER [incremental cost effectiveness ratio]) and enhance our ability to provide optimal, costeffective care for our patients.

TABLE 4. Comparison of Health Utility States

and Post-Treatment Utilities Across Disease Types

Health State

Utility

Single level cervical DDD

0.54

After single level ACDF

0.71

4

4 4

After single level CTDR

0.72

Two-level cervical DDD

0.55

After two-level ACDF

0.71

After Two-Level Ctdr

0.78

No light perception visual acuity

0.29

17

After minor stroke

0.71

17

After major stroke

0.32

After lumbar discectomy for intervertebral disc herniation18

0.84

Heart failure19

0.67

16

After pediatric heart transplant

20

0.87

DDD indicates degenerative disc disease; ACDF, anterior cervical discectomy and fusion; CTDR, cervical total disc replacement.

➢ Key Points ‰ CTDR seems to be a viable alternative for patients experiencing multilevel disc disease. Spine

‰ Quality of life was significantly better for the CTDR than that for the ACDF at every time point assessed (6–60 mo). ‰ There is value in identifying utility-associated health states for patients with cervical spine disease because it allows for quantitative categorization and longitudinal assessment of quality of life.

Supplemental digital content is available for this article. Direct URL citations appearing in the printed text are provided in the HTML and PDF version of this article on the journal’s Web site (www.spinejournal.com).

References

1. Gold MR, Siegel JE, Russell LB, et al. Cost-effectiveness in Health and Medicine. New York, NY: Oxford University Press; 1996:1–413. 2. Wakker P, Sitggelbout A. Explaining distortions in utility elicitation through the rank-dependent model for risky choices. Med Decis Making 1995;15:180–6. 3. Ament JD, Kim KD. Standardizing cost-utility analysis in neurosurgery. Neurosurg Focus 2012;33:E4. 4. Qureshi S, Goz V, McAnany S, et al. Health state utility of patients with single-level cervical degenerative disc disease: comparison of anterior cervical discectomy and fusion with cervical disc arthroplasty. J Neurosurg Spine 2014;20:475–9. 5. Lundine KM, Davis G, Rogers M, et al. Prevalence of adjacent segment disc degeneration in patients undergoing anterior cervical discectomy and fusion based on pre-operative MRI findings. J Clin Neurosci 2014;21:82–5. 6. Davis RJ, Kim KD, Hisey MS, et al. Cervical total disc replacement with Mobi-C® Cervical Artificial Disc versus anterior discectomy and fusion for the treatment of two-level symptomatic degenerative disc disease: a prospective, randomized, controlled multicenter clinical trial. J Neurosurg Spine 2013;19:432–45. 7. Gandek B, Ware JE, Aaronson NK, et al. Cross-validation of item selection and scoring for the SF-12 Health Survey in nine countries: results from the IQOLA Project. International Quality of Life Assessment. J Clin Epidemiol 1998;51:1171–8. 8. Brazier J, Roberts J, Deverill M. The estimation of a preference-based measure of health from the SF-36. J Health Econ 2002;21:271–92. 9. Bharmal M, Thomas J III. Comparing the EQ-5D and the SF-6D descriptive systems to assess their ceiling effects in the US general population. Value Health 2006;9:262–71. 10. SF-6D mapping algorithm. University of Sheffield. Available at: http://www.shef.ac.uk/scharr/sections/heds/mvh/sf-6d. 11. Vernon H, Mior S. The Neck Disability Index: a study of reliability and validity. J Manipulative Physiol Ther 1991;14:409–15. www.spinejournal.com

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CERVICAL SPINE 12. Heller JG, Sasso RC, Papadopoulos SM, et al. Comparison of BRYAN cervical disc arthroplasty with anterior cervical decompression and fusion: clinical and radiographic results of a randomized, controlled, clinical trial. Spine (Phila Pa 1976) 2009;34:101–7. 13. Goffin J, Van Calenbergh F, van Loon J, et al. Intermediate followup after treatment of degenerative disc disease with the Bryan Cervical Disc Prosthesis: single-level and bi-level. Spine (Phila Pa 1976) 2003;28:2673–8. 14. Phillips FM, Tzermiadianos MN, Voronov LI, et al. Effect of twolevel total disc replacement on cervical spine kinematics. Spine (Phila Pa 1976) 2009;34:E794–799. 15. Pimenta L, McAfee PC, Cappuccino A, et al. Superiority of multilevel cervical arthroplasty outcomes versus single-level outcomes: 229 consecutive PCM prostheses. Spine (Phila Pa 1976) 2007;32: 1337–44.

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16. Ament JD, Stryjewki TP, Chodosh J, et al. Cost-effectiveness of the Boston keratoprosthesis. Am J Ophthalmol 2010;149: 221–8. 17. Post PN, Stiggelbout AM, Wakker PP. The utility of health states after stroke. a systematic review of the literature. Stroke 2001;32:1425–9. 18. Tosteson ANA, Skinner JS, Tosteson TD, et al. The cost effectiveness of surgical versus nonoperative treatment for lumbar disc herniation over two years. Evidence from the Spine Patient Outcomes Research Trial (SPORT). Spine 2008;33:2108–15. 19. Spertus J, Peterson E, Conard MW, et al. Monitoring clinical changes in patients with heart failure: a comparison of methods. Am Heart J 2005;150:707–15. 20. Dayton JD, Kanter KR, Vincent RN, et al. Cost-effectiveness of pediatric heart transplantation. J Heart Lung Transplant 2006;25:409–15.

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A Novel Quality-of-Life Utility Index in Patients With Multilevel Cervical Degenerative Disc Disease  

A Novel Quality-of-Life Utility Index in Patients With Multilevel Cervical Degenerative Disc Disease  

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