Natália Araújo1, Milton Severo2, Luisa Lopes-Conceição3, Filipa Fontes4, Teresa Dias5, Mariana Branco6, Samantha Morais2, Vítor Tedim Cruz7, Luis Ruano8, Susana Pereira3, Nuno Lunet9. 1. EPIUnit - Instituto de Saúde Pública, Universidade do Porto, Rua das Taipas, 135, 4050-600, Porto, Portugal; Laboratório para a Investigação Integrativa e Translacional em Saúde Populacional (ITR), Rua das Taipas, 135, 4050-600, Porto, Portugal. 2. EPIUnit - Instituto de Saúde Pública, Universidade do Porto, Rua das Taipas, 135, 4050-600, Porto, Portugal; Laboratório para a Investigação Integrativa e Translacional em Saúde Populacional (ITR), Rua das Taipas, 135, 4050-600, Porto, Portugal; Departamento de Ciências da Saúde Pública e Forenses e Educação Médica, Faculdade de Medicina da Universidade do Porto, Alameda Professor Hernâni Monteiro, 4200-319, Porto, Portugal. 3. EPIUnit - Instituto de Saúde Pública, Universidade do Porto, Rua das Taipas, 135, 4050-600, Porto, Portugal; Laboratório para a Investigação Integrativa e Translacional em Saúde Populacional (ITR), Rua das Taipas, 135, 4050-600, Porto, Portugal; Instituto Português de Oncologia do Porto Francisco Gentil, Rua Dr. António Bernardino de Almeida, 4200-072, Porto, Portugal. 4. EPIUnit - Instituto de Saúde Pública, Universidade do Porto, Rua das Taipas, 135, 4050-600, Porto, Portugal; Laboratório para a Investigação Integrativa e Translacional em Saúde Populacional (ITR), Rua das Taipas, 135, 4050-600, Porto, Portugal; Departamento de Ciências da Saúde Pública e Forenses e Educação Médica, Faculdade de Medicina da Universidade do Porto, Alameda Professor Hernâni Monteiro, 4200-319, Porto, Portugal; Instituto Português de Oncologia do Porto Francisco Gentil, Rua Dr. António Bernardino de Almeida, 4200-072, Porto, Portugal. 5. Instituto Português de Oncologia do Porto Francisco Gentil, Rua Dr. António Bernardino de Almeida, 4200-072, Porto, Portugal. 6. Centro Hospitalar de Entre Douro e Vouga, Rua Dr. Cândido de Pinho, 4520-211, Santa Maria da Feira, Portugal. 7. EPIUnit - Instituto de Saúde Pública, Universidade do Porto, Rua das Taipas, 135, 4050-600, Porto, Portugal; Laboratório para a Investigação Integrativa e Translacional em Saúde Populacional (ITR), Rua das Taipas, 135, 4050-600, Porto, Portugal; Hospital Pedro Hispano, Unidade Local de Saúde de Matosinhos, Rua Dr. Eduardo Torres, 4464-513, Senhora da Hora, Portugal. 8. EPIUnit - Instituto de Saúde Pública, Universidade do Porto, Rua das Taipas, 135, 4050-600, Porto, Portugal; Laboratório para a Investigação Integrativa e Translacional em Saúde Populacional (ITR), Rua das Taipas, 135, 4050-600, Porto, Portugal; Departamento de Ciências da Saúde Pública e Forenses e Educação Médica, Faculdade de Medicina da Universidade do Porto, Alameda Professor Hernâni Monteiro, 4200-319, Porto, Portugal; Centro Hospitalar de Entre Douro e Vouga, Rua Dr. Cândido de Pinho, 4520-211, Santa Maria da Feira, Portugal. 9. EPIUnit - Instituto de Saúde Pública, Universidade do Porto, Rua das Taipas, 135, 4050-600, Porto, Portugal; Laboratório para a Investigação Integrativa e Translacional em Saúde Populacional (ITR), Rua das Taipas, 135, 4050-600, Porto, Portugal; Departamento de Ciências da Saúde Pública e Forenses e Educação Médica, Faculdade de Medicina da Universidade do Porto, Alameda Professor Hernâni Monteiro, 4200-319, Porto, Portugal. Electronic address: nlunet@med.up.pt.
Abstract
PURPOSE: To identify trajectories of cognitive performance up to five years since diagnosis and their predictors, in a cohort of patients with breast cancer (BCa). METHODS: A total of 464 women with BCa admitted to the Portuguese Institute of Oncology, Porto, during 2012, were evaluated with the Montreal Cognitive Assessment (MoCA) before any treatment, and after one, three and five years. Probable cognitive impairment (PCI) at baseline was defined based on normative age- and education-specific reference values. Mclust was used to define MoCA trajectories. Receiver Operating Characteristic curves were used to assess the predictive accuracy for cognitive trajectories. RESULTS: Two trajectories were identified, one with higher scores and increasing overtime, and the other, including 25.9% of the participants, showing a continuous decline. To further characterize each trajectory, participants were also classified as scoring above or below the median baseline MoCA scores. This resulted in four groups: 1) highest baseline scores, stable overtime (0.0% with PCI); 2) lowest baseline scores (29.5% with PCI); 3) mid-range scores at baseline, increasing overtime (10.5% with PCI); 4) mid-range scores at baseline, decreasing overtime (0.0% with PCI). Adding the change in MoCA during the first year to baseline variables significantly increased the accuracy to predict the downward trajectory (area under the curve [AUC] = 0.732 vs. AUC = 0.841, P < 0.001). CONCLUSION: Four groups of patients with BCa with different cognitive performance trends were identified. The assessment of cognitive performance before treatments and after one year allows for the identification of patients more likely to have cognitive decline in the long term.
PURPOSE: To identify trajectories of cognitive performance up to five years since diagnosis and their predictors, in a cohort of patients with breast cancer (BCa). METHODS: A total of 464 women with BCa admitted to the Portuguese Institute of Oncology, Porto, during 2012, were evaluated with the Montreal Cognitive Assessment (MoCA) before any treatment, and after one, three and five years. Probable cognitive impairment (PCI) at baseline was defined based on normative age- and education-specific reference values. Mclust was used to define MoCA trajectories. Receiver Operating Characteristic curves were used to assess the predictive accuracy for cognitive trajectories. RESULTS: Two trajectories were identified, one with higher scores and increasing overtime, and the other, including 25.9% of the participants, showing a continuous decline. To further characterize each trajectory, participants were also classified as scoring above or below the median baseline MoCA scores. This resulted in four groups: 1) highest baseline scores, stable overtime (0.0% with PCI); 2) lowest baseline scores (29.5% with PCI); 3) mid-range scores at baseline, increasing overtime (10.5% with PCI); 4) mid-range scores at baseline, decreasing overtime (0.0% with PCI). Adding the change in MoCA during the first year to baseline variables significantly increased the accuracy to predict the downward trajectory (area under the curve [AUC] = 0.732 vs. AUC = 0.841, P < 0.001). CONCLUSION: Four groups of patients with BCa with different cognitive performance trends were identified. The assessment of cognitive performance before treatments and after one year allows for the identification of patients more likely to have cognitive decline in the long term.
Authors: N Araújo; A Costa; L Lopes-Conceição; A Ferreira; F Carneiro; J Oliveira; I Braga; S Morais; L Pacheco-Figueiredo; L Ruano; V T Cruz; S Pereira; N Lunet Journal: ESMO Open Date: 2022-03-07