Sex-Based Disparities in Interval Time to Receipt of Surgical Treatment of Invasive Lung Cancer in Tennessee
Discuss this preprint
Start a discussion What are Sciety discussions?Listed in
This article is not in any list yet, why not save it to one of your lists.Abstract
Background The time from diagnosis to the receipt of definitive surgical treatment can impact patients’ survival. This study examines the sex-based disparities in the interval time to receipt of surgical treatment (ITRST) of invasive lung cancer (LC). Method We analyzed retrospective Tennessee Cancer Registry data from 12,113 invasive LC patients aged 18 years or older who received surgical treatment within 52 weeks of diagnosis from 2005 to 2015. Kruskal-Wallis tests were conducted to determine the difference in ITRST within and between groups. Adjusted multivariable Cox regression analyses were conducted to examine the independent variables associated with delayed ITRST of LC among males and females. Results There was a significant difference in ITRST between males and females. Decreased risk of delay ITRST was associated with increasing age among females (adjusted hazard ratio [aHR] = 0.59–0.70; p = 0.001–0.006), but not among males. Black patients were less likely to delay surgical treatment compared to Whites (aHR = 0.76–0.81; P < 0.001). Married patients―overall (aHR = 1.23, p < 0.001), males (aHR = 1.26, p < 0.001), and females (aHR = 1.19, p = 0.008) were more likely to delay surgery than unmarried patients. Appalachian patients (overall aHR = 1.06; p = 0.026) were more likely to delay surgery compared to non-Appalachian patients. Patients with public insurance―overall (aHR = 1.30, p < 0.001), males (aHR = 1.30, p = 0.023), and females (aHR = 1.28, p = 0.025) had an increased risk of delayed surgery than those with private insurance, compared to self-pay/uninsured. Conclusion Delayed ITRST for invasive LC is more likely among males, married patients, residents of the Appalachian region, and those with public insurance. Health interventions aimed at minimizing delays should target these populations to reduce disparities.