BACKGROUND: Since survival of patients with melanoma is strongly correlated with the Breslow tumor thickness of the primary lesion, factors that influence stage at diagnosis and delay in diagnosis are considered to be crucial. To test the relationship between tumor thickness and some social and clinical variables (including diagnosis/treatment delay) and the relationship between the diagnosis/treatment delay and some clinical variables, we analyzed data on 530 patients with melanoma from our Institute. METHODS: In the analysis, Breslow tumor thickness was categorized into two categories (< or =1.49, > or =1.5). Three time intervals were examined to evaluate diagnostic delay: patient delay, time from first symptom to seeking medical advice; medical delay, time from first medical consultation to hospital admission; total delay, time from first symptom to resection. The variables evaluated in the analysis were: age at diagnosis, education, occupational status, first symptom, visibility of tumor, anatomic site, and physician who made the initial diagnosis. RESULTS: A significant risk of having a Breslow tumor thickness > or =1.5 mm was noted in patients who had a low level of education (odds ratio 3.0, 95% confidence interval 1.9-5.0) or who were unemployed (odds ratio 1.7, 95% confidence interval 1.1-2.8). With respect to patient delay, a delay >3 months for anatomic locations visible to patients was associated with significant risk (odds ratio 1.7, 95% confidence interval 1.1-2.6); with respect to medical delay, a delay >3 months was associated with a higher risk in patients examined by a dermatologist (odds ratio 2.0, 95% confidence interval 1.2-3.4). CONCLUSIONS: Our results clearly indicate that in Southern Italy poorly educated and unemployed subjects are at risk of being diagnosed at a more advanced stage, and admission to an oncological hospital causes a delay (waiting list) in the time interval related to the doctor (medical delay).
BACKGROUND: Since survival of patients with melanoma is strongly correlated with the Breslow tumor thickness of the primary lesion, factors that influence stage at diagnosis and delay in diagnosis are considered to be crucial. To test the relationship between tumor thickness and some social and clinical variables (including diagnosis/treatment delay) and the relationship between the diagnosis/treatment delay and some clinical variables, we analyzed data on 530 patients with melanoma from our Institute. METHODS: In the analysis, Breslow tumor thickness was categorized into two categories (< or =1.49, > or =1.5). Three time intervals were examined to evaluate diagnostic delay: patient delay, time from first symptom to seeking medical advice; medical delay, time from first medical consultation to hospital admission; total delay, time from first symptom to resection. The variables evaluated in the analysis were: age at diagnosis, education, occupational status, first symptom, visibility of tumor, anatomic site, and physician who made the initial diagnosis. RESULTS: A significant risk of having a Breslow tumor thickness > or =1.5 mm was noted in patients who had a low level of education (odds ratio 3.0, 95% confidence interval 1.9-5.0) or who were unemployed (odds ratio 1.7, 95% confidence interval 1.1-2.8). With respect to patient delay, a delay >3 months for anatomic locations visible to patients was associated with significant risk (odds ratio 1.7, 95% confidence interval 1.1-2.6); with respect to medical delay, a delay >3 months was associated with a higher risk in patients examined by a dermatologist (odds ratio 2.0, 95% confidence interval 1.2-3.4). CONCLUSIONS: Our results clearly indicate that in Southern Italy poorly educated and unemployed subjects are at risk of being diagnosed at a more advanced stage, and admission to an oncological hospital causes a delay (waiting list) in the time interval related to the doctor (medical delay).
Authors: Antonieta Medina-Lara; Bogdan Grigore; Ruth Lewis; Jaime Peters; Sarah Price; Paolo Landa; Sophie Robinson; Richard Neal; William Hamilton; Anne E Spencer Journal: Health Technol Assess Date: 2020-11 Impact factor: 4.014
Authors: Susan L Boone; Jerod Stapleton; Rob Turrisi; Sara Ortiz; June K Robinson; Kimberly A Mallett Journal: Australas J Dermatol Date: 2009-08 Impact factor: 2.875
Authors: R D Neal; P Tharmanathan; B France; N U Din; S Cotton; J Fallon-Ferguson; W Hamilton; A Hendry; M Hendry; R Lewis; U Macleod; E D Mitchell; M Pickett; T Rai; K Shaw; N Stuart; M L Tørring; C Wilkinson; B Williams; N Williams; J Emery Journal: Br J Cancer Date: 2015-03-31 Impact factor: 7.640