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Introduction: The reliable assessment of treatment outcomes for disease-modifying therapies (DMT) in neurodegenerative disease is challenging. The objective of this paper is to describe a generalized framework for developing composite scales that can be applied in diverse, degenerative conditions, termed “GENCOMS.” Composite scales optimize the sensitivity for detecting clinically meaningful effects that slow disease progression.The GENCOMS method relies on robust natural history data and/or placebo arm data from DMT trials. Validated scales that are core to the disease process have been identified, and item level data obtained to standardize the response outcomes from 0 (best possible score) to 1 (worst possible score). A partial least squares regression analysis was conducted with temporal change as the dependent variable and change scores in standardized items as the explanatory variables. The derived model coefficients constitute a weighted sum of items that most effectively measure disease progression.The resultant composite scale was optimized to detect disease progression and can be examined in a range of slow or fast progressing populations. The scale can be used in studies with comparable patient populations as an endpoint optimized to measure disease progression and therefore ideally suited to assess treatment effects in DMTs.The methodology presented here provides a generalizable framework for developing composite scales in the assessment of neurodegenerative disease progression and evaluation of DMT effects. By objectively selecting and weighting items from previously validated measures based solely on their sensitivity to disease progression, this methodology allows for the creation of a more responsive measurement of clinical decline. This heightened sensitivity to clinical decline can be utilized to detect modest yet meaningful treatment effects in the early stages of neurogenerative diseases, when it is optimal to begin a DMT.Methods: The reliable assessment of treatment outcomes for disease-modifying therapies (DMT) in neurodegenerative disease is challenging. The objective of this paper is to describe a generalized framework for developing composite scales that can be applied in diverse, degenerative conditions, termed “GENCOMS.” Composite scales optimize the sensitivity for detecting clinically meaningful effects that slow disease progression.The GENCOMS method relies on robust natural history data and/or placebo arm data from DMT trials. Validated scales that are core to the disease process have been identified, and item level data obtained to standardize the response outcomes from 0 (best possible score) to 1 (worst possible score). A partial least squares regression analysis was conducted with temporal change as the dependent variable and change scores in standardized items as the explanatory variables. The derived model coefficients constitute a weighted sum of items that most effectively measure disease progression.The resultant composite scale was optimized to detect disease progression and can be examined in a range of slow or fast progressing populations. The scale can be used in studies with comparable patient populations as an endpoint optimized to measure disease progression and therefore ideally suited to assess treatment effects in DMTs.The methodology presented here provides a generalizable framework for developing composite scales in the assessment of neurodegenerative disease progression and evaluation of DMT effects. By objectively selecting and weighting items from previously validated measures based solely on their sensitivity to disease progression, this methodology allows for the creation of a more responsive measurement of clinical decline. This heightened sensitivity to clinical decline can be utilized to detect modest yet meaningful treatment effects in the early stages of neurogenerative diseases, when it is optimal to begin a DMT.Results: The reliable assessment of treatment outcomes for disease-modifying therapies (DMT) in neurodegenerative disease is challenging. The objective of this paper is to describe a generalized framework for developing composite scales that can be applied in diverse, degenerative conditions, termed “GENCOMS.” Composite scales optimize the sensitivity for detecting clinically meaningful effects that slow disease progression.The GENCOMS method relies on robust natural history data and/or placebo arm data from DMT trials. Validated scales that are core to the disease process have been identified, and item level data obtained to standardize the response outcomes from 0 (best possible score) to 1 (worst possible score). A partial least squares regression analysis was conducted with temporal change as the dependent variable and change scores in standardized items as the explanatory variables. The derived model coefficients constitute a weighted sum of items that most effectively measure disease progression.The resultant composite scale was optimized to detect disease progression and can be examined in a range of slow or fast progressing populations. The scale can be used in studies with comparable patient populations as an endpoint optimized to measure disease progression and therefore ideally suited to assess treatment effects in DMTs.The methodology presented here provides a generalizable framework for developing composite scales in the assessment of neurodegenerative disease progression and evaluation of DMT effects. By objectively selecting and weighting items from previously validated measures based solely on their sensitivity to disease progression, this methodology allows for the creation of a more responsive measurement of clinical decline. This heightened sensitivity to clinical decline can be utilized to detect modest yet meaningful treatment effects in the early stages of neurogenerative diseases, when it is optimal to begin a DMT.Conclusion: The reliable assessment of treatment outcomes for disease-modifying therapies (DMT) in neurodegenerative disease is challenging. The objective of this paper is to describe a generalized framework for developing composite scales that can be applied in diverse, degenerative conditions, termed “GENCOMS.” Composite scales optimize the sensitivity for detecting clinically meaningful effects that slow disease progression.The GENCOMS method relies on robust natural history data and/or placebo arm data from DMT trials. Validated scales that are core to the disease process have been identified, and item level data obtained to standardize the response outcomes from 0 (best possible score) to 1 (worst possible score). A partial least squares regression analysis was conducted with temporal change as the dependent variable and change scores in standardized items as the explanatory variables. The derived model coefficients constitute a weighted sum of items that most effectively measure disease progression.The resultant composite scale was optimized to detect disease progression and can be examined in a range of slow or fast progressing populations. The scale can be used in studies with comparable patient populations as an endpoint optimized to measure disease progression and therefore ideally suited to assess treatment effects in DMTs.The methodology presented here provides a generalizable framework for developing composite scales in the assessment of neurodegenerative disease progression and evaluation of DMT effects. By objectively selecting and weighting items from previously validated measures based solely on their sensitivity to disease progression, this methodology allows for the creation of a more responsive measurement of clinical decline. This heightened sensitivity to clinical decline can be utilized to detect modest yet meaningful treatment effects in the early stages of neurogenerative diseases, when it is optimal to begin a DMT. [ABSTRACT FROM AUTHOR]