Prediction of pain center treatment outcome for geriatric chronic pain patients

R. B. Cutler, David A Fishbain, Y. Lu, R. S. Rosomoff, H. L. Rosomoff

Research output: Contribution to journalArticle

16 Citations (Scopus)

Abstract

Objective: Geriatric chronic pain patients (age 65 and over) form an increasing percentage of the pain center treatment population. It is therefore important to be able to predict pain center treatment success or failure for these patients; this is the first study to address this concern. Design: Chronic pain patients rated themselves at pain center admission and discharge on 43 rating scales for the areas of pain, functional status, behavioral variables, and other pain center modification categories. The 43 scores at admission were used as potential predictors, while the 43 change scores (from admission to discharge) were the outcome measures to be predicted. Additional possible predictors were 16 other variables that are considered prognostic of treatment outcome, including age, number of surgeries, and prior occupational level. The statistical analysis consisted of a five-step procedure: (a) mathematical techniques were used to remove redundant outcome measures; (b) each of the remaining outcome variables was correlated with the full set of predictor variables; (c) regression techniques were used to predict the outcome variables; (d) these outcome variables were combined into independent factors using factor analysis; and (e) regression techniques were used to predict the factors. Results: The variable-reduction technique was successful in removing 26 of the 43 outcome variables. Factor analysis of change scores of the remaining variables resulted in four factors, which were identified as change in activity, change in pain and behavior, change in constant pain, and change in attitude to pain center goals. The analysis showed that the best predictor of a variable's change score was the initial level of that variable. Regression analysis, using all variables as predictors except initial level, found a number of statistically significant predictors. However, no predictor variable, alone or in combination, was able to account for >30% of the variance of any outcome measure. Conclusion: These results indicate that we cannot as yet predict geriatric pain center treatment outcome. Potential reasons for these results are discussed.

Original languageEnglish
Pages (from-to)10-17
Number of pages8
JournalClinical Journal of Pain
Volume10
Issue number1
StatePublished - Jan 1 1994

Fingerprint

Pain Clinics
Chronic Pain
Geriatrics
Outcome Assessment (Health Care)
Pain
Statistical Factor Analysis
Regression Analysis
Therapeutics
Population

Keywords

  • Geriatric
  • Nonsurgical techniques
  • Outcome
  • Pain center
  • Prediction
  • Treatment

ASJC Scopus subject areas

  • Anesthesiology and Pain Medicine
  • Clinical Neurology

Cite this

Cutler, R. B., Fishbain, D. A., Lu, Y., Rosomoff, R. S., & Rosomoff, H. L. (1994). Prediction of pain center treatment outcome for geriatric chronic pain patients. Clinical Journal of Pain, 10(1), 10-17.

Prediction of pain center treatment outcome for geriatric chronic pain patients. / Cutler, R. B.; Fishbain, David A; Lu, Y.; Rosomoff, R. S.; Rosomoff, H. L.

In: Clinical Journal of Pain, Vol. 10, No. 1, 01.01.1994, p. 10-17.

Research output: Contribution to journalArticle

Cutler, RB, Fishbain, DA, Lu, Y, Rosomoff, RS & Rosomoff, HL 1994, 'Prediction of pain center treatment outcome for geriatric chronic pain patients', Clinical Journal of Pain, vol. 10, no. 1, pp. 10-17.
Cutler RB, Fishbain DA, Lu Y, Rosomoff RS, Rosomoff HL. Prediction of pain center treatment outcome for geriatric chronic pain patients. Clinical Journal of Pain. 1994 Jan 1;10(1):10-17.
Cutler, R. B. ; Fishbain, David A ; Lu, Y. ; Rosomoff, R. S. ; Rosomoff, H. L. / Prediction of pain center treatment outcome for geriatric chronic pain patients. In: Clinical Journal of Pain. 1994 ; Vol. 10, No. 1. pp. 10-17.
@article{b49b9733be9243ee85694a31521a2081,
title = "Prediction of pain center treatment outcome for geriatric chronic pain patients",
abstract = "Objective: Geriatric chronic pain patients (age 65 and over) form an increasing percentage of the pain center treatment population. It is therefore important to be able to predict pain center treatment success or failure for these patients; this is the first study to address this concern. Design: Chronic pain patients rated themselves at pain center admission and discharge on 43 rating scales for the areas of pain, functional status, behavioral variables, and other pain center modification categories. The 43 scores at admission were used as potential predictors, while the 43 change scores (from admission to discharge) were the outcome measures to be predicted. Additional possible predictors were 16 other variables that are considered prognostic of treatment outcome, including age, number of surgeries, and prior occupational level. The statistical analysis consisted of a five-step procedure: (a) mathematical techniques were used to remove redundant outcome measures; (b) each of the remaining outcome variables was correlated with the full set of predictor variables; (c) regression techniques were used to predict the outcome variables; (d) these outcome variables were combined into independent factors using factor analysis; and (e) regression techniques were used to predict the factors. Results: The variable-reduction technique was successful in removing 26 of the 43 outcome variables. Factor analysis of change scores of the remaining variables resulted in four factors, which were identified as change in activity, change in pain and behavior, change in constant pain, and change in attitude to pain center goals. The analysis showed that the best predictor of a variable's change score was the initial level of that variable. Regression analysis, using all variables as predictors except initial level, found a number of statistically significant predictors. However, no predictor variable, alone or in combination, was able to account for >30{\%} of the variance of any outcome measure. Conclusion: These results indicate that we cannot as yet predict geriatric pain center treatment outcome. Potential reasons for these results are discussed.",
keywords = "Geriatric, Nonsurgical techniques, Outcome, Pain center, Prediction, Treatment",
author = "Cutler, {R. B.} and Fishbain, {David A} and Y. Lu and Rosomoff, {R. S.} and Rosomoff, {H. L.}",
year = "1994",
month = "1",
day = "1",
language = "English",
volume = "10",
pages = "10--17",
journal = "Clinical Journal of Pain",
issn = "0749-8047",
publisher = "Lippincott Williams and Wilkins",
number = "1",

}

TY - JOUR

T1 - Prediction of pain center treatment outcome for geriatric chronic pain patients

AU - Cutler, R. B.

AU - Fishbain, David A

AU - Lu, Y.

AU - Rosomoff, R. S.

AU - Rosomoff, H. L.

PY - 1994/1/1

Y1 - 1994/1/1

N2 - Objective: Geriatric chronic pain patients (age 65 and over) form an increasing percentage of the pain center treatment population. It is therefore important to be able to predict pain center treatment success or failure for these patients; this is the first study to address this concern. Design: Chronic pain patients rated themselves at pain center admission and discharge on 43 rating scales for the areas of pain, functional status, behavioral variables, and other pain center modification categories. The 43 scores at admission were used as potential predictors, while the 43 change scores (from admission to discharge) were the outcome measures to be predicted. Additional possible predictors were 16 other variables that are considered prognostic of treatment outcome, including age, number of surgeries, and prior occupational level. The statistical analysis consisted of a five-step procedure: (a) mathematical techniques were used to remove redundant outcome measures; (b) each of the remaining outcome variables was correlated with the full set of predictor variables; (c) regression techniques were used to predict the outcome variables; (d) these outcome variables were combined into independent factors using factor analysis; and (e) regression techniques were used to predict the factors. Results: The variable-reduction technique was successful in removing 26 of the 43 outcome variables. Factor analysis of change scores of the remaining variables resulted in four factors, which were identified as change in activity, change in pain and behavior, change in constant pain, and change in attitude to pain center goals. The analysis showed that the best predictor of a variable's change score was the initial level of that variable. Regression analysis, using all variables as predictors except initial level, found a number of statistically significant predictors. However, no predictor variable, alone or in combination, was able to account for >30% of the variance of any outcome measure. Conclusion: These results indicate that we cannot as yet predict geriatric pain center treatment outcome. Potential reasons for these results are discussed.

AB - Objective: Geriatric chronic pain patients (age 65 and over) form an increasing percentage of the pain center treatment population. It is therefore important to be able to predict pain center treatment success or failure for these patients; this is the first study to address this concern. Design: Chronic pain patients rated themselves at pain center admission and discharge on 43 rating scales for the areas of pain, functional status, behavioral variables, and other pain center modification categories. The 43 scores at admission were used as potential predictors, while the 43 change scores (from admission to discharge) were the outcome measures to be predicted. Additional possible predictors were 16 other variables that are considered prognostic of treatment outcome, including age, number of surgeries, and prior occupational level. The statistical analysis consisted of a five-step procedure: (a) mathematical techniques were used to remove redundant outcome measures; (b) each of the remaining outcome variables was correlated with the full set of predictor variables; (c) regression techniques were used to predict the outcome variables; (d) these outcome variables were combined into independent factors using factor analysis; and (e) regression techniques were used to predict the factors. Results: The variable-reduction technique was successful in removing 26 of the 43 outcome variables. Factor analysis of change scores of the remaining variables resulted in four factors, which were identified as change in activity, change in pain and behavior, change in constant pain, and change in attitude to pain center goals. The analysis showed that the best predictor of a variable's change score was the initial level of that variable. Regression analysis, using all variables as predictors except initial level, found a number of statistically significant predictors. However, no predictor variable, alone or in combination, was able to account for >30% of the variance of any outcome measure. Conclusion: These results indicate that we cannot as yet predict geriatric pain center treatment outcome. Potential reasons for these results are discussed.

KW - Geriatric

KW - Nonsurgical techniques

KW - Outcome

KW - Pain center

KW - Prediction

KW - Treatment

UR - http://www.scopus.com/inward/record.url?scp=0028331929&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0028331929&partnerID=8YFLogxK

M3 - Article

C2 - 7514913

AN - SCOPUS:0028331929

VL - 10

SP - 10

EP - 17

JO - Clinical Journal of Pain

JF - Clinical Journal of Pain

SN - 0749-8047

IS - 1

ER -