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New GOLD classification: longitudinal data on group assignment.

ABSTRACT: Little is known about the longitudinal changes associated with using the 2013 update of the multidimensional GOLD strategy for chronic obstructive pulmonary disease (COPD).To determine the COPD patient distribution of the new GOLD proposal and evaluate how this classification changes over one year compared with the previous GOLD staging based on spirometry only.We analyzed data from the CHAIN study, a multicenter observational Spanish cohort of COPD patients who are monitored annually. Categories were defined according to the proposed GOLD: FEV1%, mMRC dyspnea, COPD Assessment Test (CAT), Clinical COPD Questionnaire (CCQ), and exacerbations-hospitalizations. One-year follow-up information was available for all variables except CCQ data.At baseline, 828 stable COPD patients were evaluated. On the basis of mMRC dyspnea versus CAT, the patients were distributed as follows: 38.2% vs. 27.2% in group A, 17.6% vs. 28.3% in group B, 15.8% vs. 12.9% in group C, and 28.4% vs. 31.6% in group D. Information was available for 526 patients at one year: 64.2% of patients remained in the same group but groups C and D show different degrees of variability. The annual progression by group was mainly associated with one-year changes in CAT scores (RR, 1.138; 95%CI: 1.074-1.206) and BODE index values (RR, 2.012; 95%CI: 1.487-2.722).In the new GOLD grading classification, the type of tool used to determine the level of symptoms can substantially alter the group assignment. A change in category after one year was associated with longitudinal changes in the CAT and BODE index.

SUBMITTER: Casanova C

PROVIDER: S-EPMC3900265 | biostudies-literature | 2014 Jan

REPOSITORIES: biostudies-literature

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New GOLD classification: longitudinal data on group assignment.

Casanova Ciro C Marin Jose M JM Martinez-Gonzalez Cristina C de Lucas-Ramos Pilar P Mir-Viladrich Isabel I Cosio Borja B Peces-Barba German G Calle-Rubio Miryam M Solanes-García Ingrid I Agüero Ramón R de Diego-Damia Alfredo A Feu-Collado Nuria N Alfageme Inmaculada I Irigaray Rosa R Balcells Eva E Llunell Antonia A Galdiz Juan Bautista JB Marín Margarita M Soler-Cataluña Juan José JJ Lopez-Campos Jose Luis JL Soriano Joan B JB de-Torres Juan P JP

Respiratory research 20140113

<h4>Rationale</h4>Little is known about the longitudinal changes associated with using the 2013 update of the multidimensional GOLD strategy for chronic obstructive pulmonary disease (COPD).<h4>Objective</h4>To determine the COPD patient distribution of the new GOLD proposal and evaluate how this classification changes over one year compared with the previous GOLD staging based on spirometry only.<h4>Methods</h4>We analyzed data from the CHAIN study, a multicenter observational Spanish cohort of ...[more]

PMID: 24417879

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Project description:BackgroundResidual feed intake (RFI) is one measure of feed efficiency, which is usually obtained by multiple regression of feed intake (FI) on measures of production, body weight gain and tissue composition. If phenotypic regression is used, the resulting RFI is generally not genetically independent of production traits, whereas if RFI is computed using genetic regression coefficients, RFI and production traits are independent at the genetic level. The corresponding regression coefficients can be easily derived from the result of a multiple trait model that includes FI and production traits. However, this approach is difficult to apply in the case of multiple repeated measurements of FI and production traits. To overcome this difficulty, we used a structured antedependence approach to account for the longitudinality of the data with a phenotypic regression model or with different genetic and environmental regression coefficients [multi- structured antedependence model (SAD) regression model].ResultsAfter demonstrating the properties of RFI obtained by the multi-SAD regression model, we applied the two models to FI and production traits that were recorded for 2435 French Large White pigs over a 10-week period. Heritability estimates were moderate with both models. With the multi-SAD regression model, heritability estimates were quite stable over time, ranging from 0.14 ± 0.04 to 0.16 ± 0.05, while heritability estimates showed a U-shaped profile with the phenotypic regression model (ranging from 0.19 ± 0.06 to 0.28 ± 0.06). Estimates of genetic correlations between RFI at different time points followed the same pattern for the two models but higher estimates were obtained with the phenotypic regression model. Estimates of breeding values that can be used for selection were obtained by eigen-decomposition of the genetic covariance matrix. Correlations between these estimated breeding values obtained with the two models ranged from 0.66 to 0.83.ConclusionsThe multi-SAD model is preferred for the genetic analysis of longitudinal RFI because, compared to the phenotypic regression model, it provides RFI that are genetically independent of production traits at all time points. Furthermore, it can be applied even when production records are missing at certain time points.

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New GOLD classification: longitudinal data on group assignment.

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New GOLD classification: longitudinal data on group assignment.

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