OBJECTIVE: To analyze the role of sociodemographic factors as determinants of the initial pattern of care and survival in incident NSCLC cases. METHODS: We linked 2298 incident NSCLC cases, identified by the Piedmont Cancer Registry of Turin (PCRT) with administrative health records to identify the initial pattern of care. Because stage of disease strongly influences pattern of care and prognosis of NSCLC, all the analyses were stratified according to stage (early and advanced). The association between the set of patient's characteristics and the probability of accessing a specific pattern of care was analysed with a multivariable multinomial logistic regression model. Survival was analysed with the Cox proportional hazard model. RESULTS: In the early stage group, presence of comorbidities, older age and low educational level were all associated with a lower probability of receiving surgery. These same factors, as well as being unmarried, were associated with higher probability of receiving other non-curative care only. The effects of comorbidities and low educational level as barriers to receiving more effective patterns of care were not relevant in the advanced stage group. When controlling for initial patterns of care, in the early stage group, an age older than 75 years and being unmarried were negative prognostic factors, while survival was completely independent from educational level. Among patients with an advanced stage of disease, only comorbidities had a negative impact on survival. CONCLUSION: Appropriate lung cancer care is affected by sociodemographic factors. Greater attention to social and health programs is recommended to improve the timeliness of diagnosis, the staging of potentially resectable patients, and to implement more comprehensive multidisciplinary evaluations of those who may benefit from curative treatments.
OBJECTIVE: To analyze the role of sociodemographic factors as determinants of the initial pattern of care and survival in incident NSCLC cases. METHODS: We linked 2298 incident NSCLC cases, identified by the Piedmont Cancer Registry of Turin (PCRT) with administrative health records to identify the initial pattern of care. Because stage of disease strongly influences pattern of care and prognosis of NSCLC, all the analyses were stratified according to stage (early and advanced). The association between the set of patient's characteristics and the probability of accessing a specific pattern of care was analysed with a multivariable multinomial logistic regression model. Survival was analysed with the Cox proportional hazard model. RESULTS: In the early stage group, presence of comorbidities, older age and low educational level were all associated with a lower probability of receiving surgery. These same factors, as well as being unmarried, were associated with higher probability of receiving other non-curative care only. The effects of comorbidities and low educational level as barriers to receiving more effective patterns of care were not relevant in the advanced stage group. When controlling for initial patterns of care, in the early stage group, an age older than 75 years and being unmarried were negative prognostic factors, while survival was completely independent from educational level. Among patients with an advanced stage of disease, only comorbidities had a negative impact on survival. CONCLUSION: Appropriate lung cancer care is affected by sociodemographic factors. Greater attention to social and health programs is recommended to improve the timeliness of diagnosis, the staging of potentially resectable patients, and to implement more comprehensive multidisciplinary evaluations of those who may benefit from curative treatments.
Authors: Leah L Zullig; William R Carpenter; Dawn T Provenzale; Morris Weinberger; Bryce B Reeve; Christina D Williams; George L Jackson Journal: Cancer Manag Res Date: 2013-07-24 Impact factor: 3.989
Authors: E Chatzimichail; D Matthaios; D Bouros; P Karakitsos; K Romanidis; S Kakolyris; G Papashinopoulos; A Rigas Journal: Int J Genomics Date: 2014-01-08 Impact factor: 2.326