BACKGROUND: The potential impact of diagnostic delays on patients' outcomes is a debated issue in pediatric oncology and discordant results have been published so far. We attempted to tackle this issue by analyzing a prospective series of 351 consecutive children and adolescents with solid malignancies using innovative statistical tools. METHODS: To address the nonlinear complexity of the association between symptom interval and overall survival (OS), a regression tree algorithm was constructed with sequential binary splitting rules and used to identify homogeneous patient groups vis-à-vis functional relationship between diagnostic delay and OS. RESULTS: Three different groups were identified: group A, with localized disease and good prognosis (5-year OS 85.4%); group B, with locally or regionally advanced, or metastatic disease and intermediate prognosis (5-year OS 72.9%), including neuroblastoma, Wilms tumor, non-rhabdomyosarcoma soft tissue sarcoma, and germ cell tumor; and group C, with locally or regionally advanced, or metastatic disease and poor prognosis (5-year OS 45%), including brain tumors, rhabdomyosarcoma, and bone sarcoma. The functional relationship between symptom interval and mortality risk differed between the three subgroups, there being no association in group A (hazard ratio [HR]: 0.96), a positive linear association in group B (HR: 1.48), and a negative linear association in group C (HR: 0.61). CONCLUSIONS: Our analysis suggests that at least a subset of patients can benefit from an earlier diagnosis in terms of survival. For others, intrinsic aggressiveness may mask the potential effect of diagnostic delays. Based on these findings, early diagnosis should remain a goal for pediatric cancer patients.
BACKGROUND: The potential impact of diagnostic delays on patients' outcomes is a debated issue in pediatric oncology and discordant results have been published so far. We attempted to tackle this issue by analyzing a prospective series of 351 consecutive children and adolescents with solid malignancies using innovative statistical tools. METHODS: To address the nonlinear complexity of the association between symptom interval and overall survival (OS), a regression tree algorithm was constructed with sequential binary splitting rules and used to identify homogeneous patient groups vis-à-vis functional relationship between diagnostic delay and OS. RESULTS: Three different groups were identified: group A, with localized disease and good prognosis (5-year OS 85.4%); group B, with locally or regionally advanced, or metastatic disease and intermediate prognosis (5-year OS 72.9%), including neuroblastoma, Wilms tumor, non-rhabdomyosarcoma soft tissue sarcoma, and germ cell tumor; and group C, with locally or regionally advanced, or metastatic disease and poor prognosis (5-year OS 45%), including brain tumors, rhabdomyosarcoma, and bone sarcoma. The functional relationship between symptom interval and mortality risk differed between the three subgroups, there being no association in group A (hazard ratio [HR]: 0.96), a positive linear association in group B (HR: 1.48), and a negative linear association in group C (HR: 0.61). CONCLUSIONS: Our analysis suggests that at least a subset of patients can benefit from an earlier diagnosis in terms of survival. For others, intrinsic aggressiveness may mask the potential effect of diagnostic delays. Based on these findings, early diagnosis should remain a goal for pediatric cancerpatients.
Authors: Teresa de Rojas; Francisco Bautista; Miguel Flores; Lucía Igual; Raquel Rubio; Eduardo Bardón; Lucía Navarro; Laura Murillo; Raquel Hladun; Adela Cañete; Miguel Garcia-Ariza; Carmen Garrido; Ana Fernández-Teijeiro; Eduardo Quiroga; Carlota Calvo; Anna Llort; Inmaculada de Prada; Luis Madero; Ofelia Cruz; Lucas Moreno Journal: J Neurooncol Date: 2017-12-16 Impact factor: 4.130
Authors: Eduardo Javier Barragán-Pérez; Carlos Enrique Altamirano-Vergara; Daniel Eduardo Alvarez-Amado; Juan Carlos García-Beristain; Fernando Chico-Ponce-de-León; Vicente González-Carranza; Luis Juárez-Villegas; Chiharu Murata Journal: Pathol Oncol Res Date: 2020-07-13 Impact factor: 2.874
Authors: Silvia Triarico; Michele Antonio Capozza; Stefano Mastrangelo; Giorgio Attinà; Palma Maurizi; Antonio Ruggiero Journal: Ann Transl Med Date: 2020-03