A predictive model and nomogram for predicting return to work at 3 months after cervical spine surgery

An analysis from the Quality Outcomes Database

Clinton J. Devin, Mohamad Bydon, Mohammed Ali Alvi, Panagiotis Kerezoudis, Inamullah Khan, Ahilan Sivaganesan, Matthew J. McGirt, Kristin R. Archer, Kevin Foley, Praveen V. Mummaneni, Erica F. Bisson, John J. Knightly, Christopher I. Shaffrey, Anthony L. Asher

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

OBJECTIVE Back pain and neck pain are two of the most common causes of work loss due to disability, which poses an economic burden on society. Due to recent changes in healthcare policies, patient-centered outcomes including return to work have been increasingly prioritized by physicians and hospitals to optimize healthcare delivery. In this study, the authors used a national spine registry to identify clinical factors associated with return to work at 3 months among patients undergoing a cervical spine surgery. METHODS The authors queried the Quality Outcomes Database registry for information collected from April 2013 through March 2017 for preoperatively employed patients undergoing cervical spine surgery for degenerative spine disease. Covariates included demographic, clinical, and operative variables, and baseline patient-reported outcomes. Multiple imputations were used for missing values and multivariable logistic regression analysis was used to identify factors associated with higher odds of returning to work. Bootstrap resampling (200 iterations) was used to assess the validity of the model. A nomogram was constructed using the results of the multivariable model. RESULTS A total of 4689 patients were analyzed, of whom 82.2% (n = 3854) returned to work at 3 months postoperatively. Among previously employed and working patients, 89.3% (n = 3443) returned to work compared to 52.3% (n = 411) among those who were employed but not working (e.g., were on a leave) at the time of surgery (p < 0.001). On multivariable logistic regression the authors found that patients who were less likely to return to work were older (age > 56-65 years: OR 0.69, 95% CI 0.57-0.85, p < 0.001; age > 65 years: OR 0.65, 95% CI 0.43-0.97, p = 0.02); were employed but not working (OR 0.24, 95% CI 0.20-0.29, p < 0.001); were employed part time (OR 0.56, 95% CI 0.42-0.76, p < 0.001); had a heavy-intensity (OR 0.42, 95% CI 0.32-0.54, p < 0.001) or medium-intensity (OR 0.59, 95% CI 0.46-0.76, p < 0.001) occupation compared to a sedentary occupation type; had workers' compensation (OR 0.38, 95% CI 0.28-0.53, p < 0.001); had a higher Neck Disability Index score at baseline (OR 0.60, 95% CI 0.51-0.70, p = 0.017); were more likely to present with myelopathy (OR 0.52, 95% CI 0.42-0.63, p < 0.001); and had more levels fused (3-5 levels: OR 0.46, 95% CI 0.35-0.61, p < 0.001). Using the multivariable analysis, the authors then constructed a nomogram to predict return to work, which was found to have an area under the curve of 0.812 and good validity. CONCLUSIONS Return to work is a crucial outcome that is being increasingly prioritized for employed patients under- going spine surgery. The results from this study could help surgeons identify at-risk patients so that preoperative expectations could be discussed more comprehensively.

Original languageEnglish (US)
Article numberE9
JournalNeurosurgical focus
Volume45
Issue number5
DOIs
StatePublished - Nov 1 2018

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Nomograms
Return to Work
Spine
Databases
Occupations
Registries
Delivery of Health Care
Workers' Compensation
Neck Pain
Spinal Cord Diseases
Back Pain
Area Under Curve
Neck
Logistic Models
Regression Analysis
Economics
Demography
Physicians

All Science Journal Classification (ASJC) codes

  • Surgery
  • Clinical Neurology

Cite this

A predictive model and nomogram for predicting return to work at 3 months after cervical spine surgery : An analysis from the Quality Outcomes Database. / Devin, Clinton J.; Bydon, Mohamad; Alvi, Mohammed Ali; Kerezoudis, Panagiotis; Khan, Inamullah; Sivaganesan, Ahilan; McGirt, Matthew J.; Archer, Kristin R.; Foley, Kevin; Mummaneni, Praveen V.; Bisson, Erica F.; Knightly, John J.; Shaffrey, Christopher I.; Asher, Anthony L.

In: Neurosurgical focus, Vol. 45, No. 5, E9, 01.11.2018.

Research output: Contribution to journalArticle

Devin, CJ, Bydon, M, Alvi, MA, Kerezoudis, P, Khan, I, Sivaganesan, A, McGirt, MJ, Archer, KR, Foley, K, Mummaneni, PV, Bisson, EF, Knightly, JJ, Shaffrey, CI & Asher, AL 2018, 'A predictive model and nomogram for predicting return to work at 3 months after cervical spine surgery: An analysis from the Quality Outcomes Database', Neurosurgical focus, vol. 45, no. 5, E9. https://doi.org/10.3171/2018.8.FOCUS18326
Devin, Clinton J. ; Bydon, Mohamad ; Alvi, Mohammed Ali ; Kerezoudis, Panagiotis ; Khan, Inamullah ; Sivaganesan, Ahilan ; McGirt, Matthew J. ; Archer, Kristin R. ; Foley, Kevin ; Mummaneni, Praveen V. ; Bisson, Erica F. ; Knightly, John J. ; Shaffrey, Christopher I. ; Asher, Anthony L. / A predictive model and nomogram for predicting return to work at 3 months after cervical spine surgery : An analysis from the Quality Outcomes Database. In: Neurosurgical focus. 2018 ; Vol. 45, No. 5.
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abstract = "OBJECTIVE Back pain and neck pain are two of the most common causes of work loss due to disability, which poses an economic burden on society. Due to recent changes in healthcare policies, patient-centered outcomes including return to work have been increasingly prioritized by physicians and hospitals to optimize healthcare delivery. In this study, the authors used a national spine registry to identify clinical factors associated with return to work at 3 months among patients undergoing a cervical spine surgery. METHODS The authors queried the Quality Outcomes Database registry for information collected from April 2013 through March 2017 for preoperatively employed patients undergoing cervical spine surgery for degenerative spine disease. Covariates included demographic, clinical, and operative variables, and baseline patient-reported outcomes. Multiple imputations were used for missing values and multivariable logistic regression analysis was used to identify factors associated with higher odds of returning to work. Bootstrap resampling (200 iterations) was used to assess the validity of the model. A nomogram was constructed using the results of the multivariable model. RESULTS A total of 4689 patients were analyzed, of whom 82.2{\%} (n = 3854) returned to work at 3 months postoperatively. Among previously employed and working patients, 89.3{\%} (n = 3443) returned to work compared to 52.3{\%} (n = 411) among those who were employed but not working (e.g., were on a leave) at the time of surgery (p < 0.001). On multivariable logistic regression the authors found that patients who were less likely to return to work were older (age > 56-65 years: OR 0.69, 95{\%} CI 0.57-0.85, p < 0.001; age > 65 years: OR 0.65, 95{\%} CI 0.43-0.97, p = 0.02); were employed but not working (OR 0.24, 95{\%} CI 0.20-0.29, p < 0.001); were employed part time (OR 0.56, 95{\%} CI 0.42-0.76, p < 0.001); had a heavy-intensity (OR 0.42, 95{\%} CI 0.32-0.54, p < 0.001) or medium-intensity (OR 0.59, 95{\%} CI 0.46-0.76, p < 0.001) occupation compared to a sedentary occupation type; had workers' compensation (OR 0.38, 95{\%} CI 0.28-0.53, p < 0.001); had a higher Neck Disability Index score at baseline (OR 0.60, 95{\%} CI 0.51-0.70, p = 0.017); were more likely to present with myelopathy (OR 0.52, 95{\%} CI 0.42-0.63, p < 0.001); and had more levels fused (3-5 levels: OR 0.46, 95{\%} CI 0.35-0.61, p < 0.001). Using the multivariable analysis, the authors then constructed a nomogram to predict return to work, which was found to have an area under the curve of 0.812 and good validity. CONCLUSIONS Return to work is a crucial outcome that is being increasingly prioritized for employed patients under- going spine surgery. The results from this study could help surgeons identify at-risk patients so that preoperative expectations could be discussed more comprehensively.",
author = "Devin, {Clinton J.} and Mohamad Bydon and Alvi, {Mohammed Ali} and Panagiotis Kerezoudis and Inamullah Khan and Ahilan Sivaganesan and McGirt, {Matthew J.} and Archer, {Kristin R.} and Kevin Foley and Mummaneni, {Praveen V.} and Bisson, {Erica F.} and Knightly, {John J.} and Shaffrey, {Christopher I.} and Asher, {Anthony L.}",
year = "2018",
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TY - JOUR

T1 - A predictive model and nomogram for predicting return to work at 3 months after cervical spine surgery

T2 - An analysis from the Quality Outcomes Database

AU - Devin, Clinton J.

AU - Bydon, Mohamad

AU - Alvi, Mohammed Ali

AU - Kerezoudis, Panagiotis

AU - Khan, Inamullah

AU - Sivaganesan, Ahilan

AU - McGirt, Matthew J.

AU - Archer, Kristin R.

AU - Foley, Kevin

AU - Mummaneni, Praveen V.

AU - Bisson, Erica F.

AU - Knightly, John J.

AU - Shaffrey, Christopher I.

AU - Asher, Anthony L.

PY - 2018/11/1

Y1 - 2018/11/1

N2 - OBJECTIVE Back pain and neck pain are two of the most common causes of work loss due to disability, which poses an economic burden on society. Due to recent changes in healthcare policies, patient-centered outcomes including return to work have been increasingly prioritized by physicians and hospitals to optimize healthcare delivery. In this study, the authors used a national spine registry to identify clinical factors associated with return to work at 3 months among patients undergoing a cervical spine surgery. METHODS The authors queried the Quality Outcomes Database registry for information collected from April 2013 through March 2017 for preoperatively employed patients undergoing cervical spine surgery for degenerative spine disease. Covariates included demographic, clinical, and operative variables, and baseline patient-reported outcomes. Multiple imputations were used for missing values and multivariable logistic regression analysis was used to identify factors associated with higher odds of returning to work. Bootstrap resampling (200 iterations) was used to assess the validity of the model. A nomogram was constructed using the results of the multivariable model. RESULTS A total of 4689 patients were analyzed, of whom 82.2% (n = 3854) returned to work at 3 months postoperatively. Among previously employed and working patients, 89.3% (n = 3443) returned to work compared to 52.3% (n = 411) among those who were employed but not working (e.g., were on a leave) at the time of surgery (p < 0.001). On multivariable logistic regression the authors found that patients who were less likely to return to work were older (age > 56-65 years: OR 0.69, 95% CI 0.57-0.85, p < 0.001; age > 65 years: OR 0.65, 95% CI 0.43-0.97, p = 0.02); were employed but not working (OR 0.24, 95% CI 0.20-0.29, p < 0.001); were employed part time (OR 0.56, 95% CI 0.42-0.76, p < 0.001); had a heavy-intensity (OR 0.42, 95% CI 0.32-0.54, p < 0.001) or medium-intensity (OR 0.59, 95% CI 0.46-0.76, p < 0.001) occupation compared to a sedentary occupation type; had workers' compensation (OR 0.38, 95% CI 0.28-0.53, p < 0.001); had a higher Neck Disability Index score at baseline (OR 0.60, 95% CI 0.51-0.70, p = 0.017); were more likely to present with myelopathy (OR 0.52, 95% CI 0.42-0.63, p < 0.001); and had more levels fused (3-5 levels: OR 0.46, 95% CI 0.35-0.61, p < 0.001). Using the multivariable analysis, the authors then constructed a nomogram to predict return to work, which was found to have an area under the curve of 0.812 and good validity. CONCLUSIONS Return to work is a crucial outcome that is being increasingly prioritized for employed patients under- going spine surgery. The results from this study could help surgeons identify at-risk patients so that preoperative expectations could be discussed more comprehensively.

AB - OBJECTIVE Back pain and neck pain are two of the most common causes of work loss due to disability, which poses an economic burden on society. Due to recent changes in healthcare policies, patient-centered outcomes including return to work have been increasingly prioritized by physicians and hospitals to optimize healthcare delivery. In this study, the authors used a national spine registry to identify clinical factors associated with return to work at 3 months among patients undergoing a cervical spine surgery. METHODS The authors queried the Quality Outcomes Database registry for information collected from April 2013 through March 2017 for preoperatively employed patients undergoing cervical spine surgery for degenerative spine disease. Covariates included demographic, clinical, and operative variables, and baseline patient-reported outcomes. Multiple imputations were used for missing values and multivariable logistic regression analysis was used to identify factors associated with higher odds of returning to work. Bootstrap resampling (200 iterations) was used to assess the validity of the model. A nomogram was constructed using the results of the multivariable model. RESULTS A total of 4689 patients were analyzed, of whom 82.2% (n = 3854) returned to work at 3 months postoperatively. Among previously employed and working patients, 89.3% (n = 3443) returned to work compared to 52.3% (n = 411) among those who were employed but not working (e.g., were on a leave) at the time of surgery (p < 0.001). On multivariable logistic regression the authors found that patients who were less likely to return to work were older (age > 56-65 years: OR 0.69, 95% CI 0.57-0.85, p < 0.001; age > 65 years: OR 0.65, 95% CI 0.43-0.97, p = 0.02); were employed but not working (OR 0.24, 95% CI 0.20-0.29, p < 0.001); were employed part time (OR 0.56, 95% CI 0.42-0.76, p < 0.001); had a heavy-intensity (OR 0.42, 95% CI 0.32-0.54, p < 0.001) or medium-intensity (OR 0.59, 95% CI 0.46-0.76, p < 0.001) occupation compared to a sedentary occupation type; had workers' compensation (OR 0.38, 95% CI 0.28-0.53, p < 0.001); had a higher Neck Disability Index score at baseline (OR 0.60, 95% CI 0.51-0.70, p = 0.017); were more likely to present with myelopathy (OR 0.52, 95% CI 0.42-0.63, p < 0.001); and had more levels fused (3-5 levels: OR 0.46, 95% CI 0.35-0.61, p < 0.001). Using the multivariable analysis, the authors then constructed a nomogram to predict return to work, which was found to have an area under the curve of 0.812 and good validity. CONCLUSIONS Return to work is a crucial outcome that is being increasingly prioritized for employed patients under- going spine surgery. The results from this study could help surgeons identify at-risk patients so that preoperative expectations could be discussed more comprehensively.

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