Adaptação transcultural do instrumento Karnofsky Performance Status para o português do Brasil
Cross-cultural adaptation of the Karnofsky Performance Status instrument to Brazilian Portuguese
Patrícia Cristina dos Santos Ferreira; Mirian Nunes Moreira; Roberto Alves Lourenço
Resumo
Introdução: O Karnofsky Performance Status (KPS) é um dos instrumentos mais utilizados para avaliação do prognóstico do paciente oncológico proporcionando a estimativa de eficiência do tratamento e sobrevida. Apesar disso, é comumente utilizado em traduções livres e sem validação. O objetivo do presente estudo foi realizar a adaptação transcultural do instrumento KPS para o português do Brasil (KPS-BR) em suas etapas de equivalências de conceito, semântica, operacional, mensuração e funcional.
Métodos: Para avaliação da consistência utilizamos os coeficientes alfa de Cronbach e kappa. Foi realizado o teste Qui-quadrado para avaliar a associação das pontuações e o número de óbitos. A relação com o tempo de sobrevida e a mortalidade foi explorada com curvas de Kaplan-Meier.
Resultados: Um total de 316 pacientes participaram do estudo. A análise de consistência interna resultou em coeficiente de confiabilidade alfa de Cronbach de 0,9265. Para análise inter-aferidor, o coeficiente de correlação foi de 1, assim como o coeficiente kappa, indicando uma concordância perfeita entre os observadores. O coeficiente de correlação entre a escala KPS-BR no teste-reteste foi de 0,8631. Observamos uma taxa de 100% de óbitos na pontuação 20 da escala KPS-BR e uma diminuição gradual à medida que a pontuação da escala KPS-BR aumenta até KPS-BR 40 (p<0,0001). A estimativa da sobrevida pelo método Kaplan-Meier mostrou uma associação entre as pontuações da escala KPS-BR e a sobrevida (p<0,0001).
Conclusão: A escala KPS-BR apresentou confiabilidade e validade para a avaliação prognóstica de pacientes com câncer, mostrando associação com a sobrevida.
Palavras-chave
Abstract
Introduction: The Karnofsky Performance Status (KPS) is one of the most widely used tools for assessing the prognosis of oncology patients, providing an estimate of treatment efficiency and survival. Despite this, it is commonly used in free translations without validation. The objective of the present study was to perform the cross-cultural adaptation of the KPS instrument to Brazilian Portuguese (KPS-BR) through the stages of conceptual, semantic, operational, measurement, and functional equivalences.
Methods: To assess consistency, we used Cronbach’s alpha and kappa coefficients. The Chi-square test was performed to evaluate the association between scores and the number of deaths. The relationship with survival and mortality was explored with Kaplan-Meier curves.
Results: A total of 316 patients participated in the study. The internal consistency analysis resulted in a Cronbach’s alpha coefficient of 0.9265. For the inter-rater analysis, the correlation coefficient was 1, as was the kappa coefficient, indicating perfect agreement between observers. The correlation coefficient between the KPS-BR scale in the test-retest was 0.8631. We observed a 100% death rate at KPS-BR scale score 20 and a gradual decrease as the KPS-BR scale score increases up to KPS-BR 40 (p<0.0001). Estimation of survival using the Kaplan-Meier method demonstrated an association between KPS-BR scale scores and survival (p<0.0001).
Conclusion: The KPS-BR scale showed reliability and validity for the prognostic assessment of cancer patients, demonstrating a correlation with survival.
Keywords
Referências
1 INCA Estimativa 2023 de Incidência de Câncer no Brasil.
2 Karnofsky DA, Abelmann WH, Craver LF, Burchenal JH. The use of the nitrogen mustards in the palliative treatment of carcinoma. Cancer. 1948;1:634-56.
3 Dzierzanowski T, Gradalski T, Kozlowski M. Palliative Performance Scale: cross cultural adaptation and psychometric validation for Polish hospice setting. BMC Palliat Care. 2020;19:52. doi: 10.1186/s12904-020-00563-8.
4 Sutherland R. Dying Well-Informed: The Need for Better Clinical Education Surrounding Facilitating End-of-Life Conversations. Yale J Biol Med. 2019;92(4):757-64.
5 Beaton D, Bombardier C, Guillemin F, Ferraz MB. Guidelines for the Process of Cross-Cultural Adaptation of Self-Report Measures. Spine. 2000;25(24):3186-91. DOI: 10.1097/00007632-200012150-00014
6 Wild D, Grove A, Martin M, Eremenco S, McElroy S, Verjee-Lorenz A, et al. Principles of Good Practice for the Translation and Cultural Adaptation Process for Patient-Reported Outcomes (PRO) Measures: Report of the ISPOR Task Force for Translation and Cultural Adaptation. Value in Health. 2005;8:94-104. doi: 10.1111/j.1524-4733.2005.04054.x.
7 Bagno M. Norma Linguística, Hibridismo e Tradução. Traduzires. 2018:1(1):19-32.
8 Reichenheim ME, Moraes CL. Operacionalização de adaptação transcultural de instrumentos de aferição usados em epidemiologia. Rev Saúde Pública. 2007;41(4):665-73. doi: 10.1590/s0034-89102006005000035.
9 Herdman M, Fox-Rushby J, Badia X. 'Equivalence' and the translation and adaptation of health-related quality of life questionnaires. Qual Life Res. 1997;6(3):237-47. doi: 10.1023/a:1026410721664.
10 Herdman M, Fox-Rushby J, Badia X. A model of equivalence in the cultural adaptation of HRQoL instruments: the universalist approach. Qual Life Res. 1998;7(4):323-35. doi: 10.1023/a:1024985930536.
11 Katz S, Ford AB, Moskowitz RW, Jackson BA, Jaffe MW. Studies of illness in the aged. The index of ADL: a standardized measure of biological and psychosocial function. JAMA. 1963;185(12):914-9. doi: 10.1001/jama.1963.03060120024016.
12 Lawton MP, Brody EM. Assessment of older people: Self-maintaining and instrumental activities of daily living. The Gerontologist. 1969;9(3):179-86.
13 Bruera E, Kuehn N, Miller MJ, Selmser P, Macmillan K. The Edmonton Symptom Assessment System (ESAS): a simple method for the assessment of palliative care patients. J Palliat Care. 1991;7:6-9.
14 RStudio Team (2020). RStudio: Integrated Development for R. RStudio, PBC, Boston, MA URL
15 Glare P, Virik K, Jones M, Hudson M, Eychmuller S, Simes J, Christakis N. A systematic review of physicians' survival predictions in terminally ill cancer patients. BMJ. 2003;327(7408):195-8. doi: 10.1136/bmj.327.7408.195.
16 De Borja MT, Chow E, Bovett G, et al. The correlation among patients and health care professionals in assessing functional status using the Karnofsky and eastern cooperative oncology group performance status scales. Support Cancer Ther. 2004;2(1):59-63. doi: 10.3816/SCT.2004.n.024.
17 Maltoni M, et al. Prognostic factors in advanced cancer patients: evidence-based clinical recommendations-a study by the steering committee of the European Association for Palliative Care. J Clin Oncol. 2005;23(25):6240-8. doi: 10.1200/JCO.2005.06.866.
18 Hui D. Prognostication of survival in patients with advanced cancer: predicting the unpredictable? Cancer Control. 2015;22(4):489-97. doi: 10.1177/107327481502200415.
19 Abernethy AP, Shelby-James T, Fazekas BS, Woods D, Currow D. The Australia-modified Karnofsky Performance Status (AKPS) scale: a revised scale for contemporary palliative care clinical practice. BMC Palliative Care. 2005;4(7):1-12. doi:10.1186/1472-684X-4-7.
20 Yates JW, Chalmer B, McKegney FP. Evaluation of patients with advanced cancer using the Karnofsky performance status. Cancer. 1980;45:2220-4. doi: 10.1002/1097-0142(19800415)45:8<2220::aid-cncr2820450835>3.0.co;2-q.
21 Huang Y, Roy N, Dhar E, Upadhyay U, Kabir MA, Uddin M, et al. Deep Learning Prediction Model for Patient Survival Outcomes in Palliative Care Using Actigraphy Data and Clinical Information. Cancers (Basel). 2023;15(8):2232. doi: 10.3390/cancers15082232.
22 Hauser CA, Stockler MR, Tattersall MH. Prognostic factors in patients with recently diagnosed incurable cancer: a systematic review. Supp Care Cancer. 2006;14:999-1011. doi: 10.1007/s00520-006-0079-9. Epub 2006 May 18.
23 Katano A, Minamitani M, Tongyu G, Ohira S, Yamashita H. Survival Following Palliative Radiotherapy for Head and Neck Squamous Cell Carcinoma: Examining Treatment Indications in Elderly Patients. Cancer Diagn Progn. 2024;4(1):46-50. doi: 10.21873/cdp.10284. eCollection 2024 Jan-Feb.
24 Natesan D, Carpenter DJ, Giles W, Oyekunle T, Niedzwiecki D, Reitman ZJ, et al. Clinical Factors Associated With 30-Day Mortality Among Patients Undergoing Radiation Therapy for Brain Metastases. Adv Radiat Oncol. 2023;8(4):101211. doi: 10.1016/j.adro.2023.101211.
25 Sperduto PW, Mesko S, Li J, Cagney D, Aizer A, Lin NU, et al. Survival in Patients With Brain Metastases: Summary Report on the Updated Diagnosis-Specific Graded Prognostic Assessment and Definition of the Eligibility Quotient. J Clin Oncol. 2020;38(32):3773-84. doi: 10.1200/JCO.20.01255.
26 Lee SS, Ahn JH, Kim MK, Sym SJ, Gong G, Do Ahn S, et al. Brain Metastases in Breast Cancer: Prognostic Factors and Management. Breast Cancer Res Treat. 2008;111(3):523-30. doi: 10.1007/s10549-007-9806-2.
27 Dyer MA, Kelly PJ, Chen YH, Pinnell NE, Claus EB, Lee EQ, et al. Importance of Extracranial Disease Status and Tumor Subtype for Patients Undergoing Radiosurgery for Breast Cancer Brain Metastases. Int J Radiat Oncol Biol Physics. 2012;83(4):e479-86. doi: 10.1016/j.ijrobp.2012.01.054.
28 Freeman M, Ennis M, Jerzak KJ. Karnofsky Performance Status (KPS) =60 Is Strongly Associated With Shorter Brain-Specific Progression-Free Survival Among Patients With Metastatic Breast Cancer With Brain Metastases. Front Oncol. 2022;12:867462. doi: 10.3389/fonc.2022.867462.
29 Lu X, Cai Y, Xia L, et al. Treatment modalities and relative survival in patients with brain metastasis from colorectal cancer. Biosci Trends. 2019;13:182-8. doi: 10.5582/bst.2019.01044.
30 Bonadio RC, Freitas GF, Batista DN, et al. Epidemiology and outcomes of patients with brain metastases from colorectal cancer - who are these patients? Clin Colorectal Cancer. 2021;20:195-200. doi: 10.1016/j.clcc.2021.04.002.
31 Li W, Wang T, Zhu Y, Yu H, Ma L, Ding Y, et al. Brain metastasis from colorectal cancer: Treatment, survival, and prognosis. Medicine (Baltimore). 2022;101(40):e30273. doi: 10.1097/MD.0000000000030273.
32 Dziggel L, Schild SE, Veninga T, Bajrovic A, Rades D. Clinical Factors Asssociated with Treatment Outcomes following Whole-brain Irradiation in Patients with Prostate Cancer. In Vivo. 2017;31(1):35-8. doi: 10.21873/invivo.11021.
33 Tobias B, Rades D. Predicting Survival after Whole-Brain Irradiation for Cerebral Metastases from Prostate Cancer. Anticancer Res. 2014;34(8):4357-60.
34 Péus D, Newcomb N, Hofer Si. Appraisal of the Karnofsky Performance Status and proposal of a simple algorithmic system for its evaluation. BMC Med Inform Decis Mak. 2013;13:72. doi: 10.1186/1472-6947-13-72.
Submetido em:
15/05/2024
Aceito em:
09/06/2024
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