Travel burdens to access care among children with cancer between 2016 and 2019: Analysis of a national population-based cancer registry in Japan

BACKGROUND

Centralization of cancer care increases survival but increases the travel burden (i.e., travel durations, distances, and expenditures) in visiting hospitals. This study investigated the travel burdens to access cancer care for children aged 18 years and younger in Japan.

METHODS

The study population comprised 10,709 patients diagnosed between 2016 and 2019 obtained from a national population-based cancer registry in Japan. Their residences were classified as urban or rural. We counted the number of patients treated at specialized hospitals and investigated the treatment centralization across diagnostic groups by Pareto plot. Travel burdens to access care were estimated using a route-planner web service and summarized using median values. A multivariable logistic model was performed to investigate factors associated with the events of car travel duration exceeding 1 h.

RESULTS

Of the patients, 76.7% lived in urban areas, and 82.5% received treatment in designated hospitals for childhood cancer. The Pareto plot suggested that the top five hospitals treated 63.5% of patients with retinoblastoma. The estimated travel burdens for all patients were 0.62 h (0.57 h in urban areas and 1.00 h in rural areas), 16.9 km, and 0.0 dollars of toll charges. Regarding travel duration, 21.7% of patients had travel exceeding 1 h, and rural areas, retinoblastoma, malignant bone tumors, and childhood cancer-hub hospitals were associated with travel duration exceeding 1 h (adjusted odds ratios of 6.93, 3.59, 1.94, and 1.91, respectively).

CONCLUSIONS

Most patients were treated in specialized hospitals and the treatments for specific diseases were centralized. However, most patients were estimated to travel less than 1 h, and the travel burden tended to increase for patients in rural areas, those with specific diseases, and those going to specialized hospitals. Cancer control measures in Japan have steadily improved centralized treatment while keeping the travel burden relatively manageable.

Factors Affecting Delay in Initial Treatment of Patients with Soft Tissue Sarcomas

Background: Soft tissue sarcomas (STS) are rare, and little is known about the factors that affect the delays in the initial treatment. The aim of this study is to quantify the period between onset of symptoms and start of treatment of STS and determine the factors affecting delays in initial treatment. Methods: This is a retrospective study of all STS treated in our institution between October 2009 and March 2019. We analysed patient record to determine the period from onset of symptoms to start of initial treatment. We also collected data with regard to patient characteristics and features of the tumour. Tumours were classified into upper extremity, lower extremity, trunk and others based on location of the tumour. Statistical tests were done to identify factors that affected delay in initial treatment. Results: The study included 134 patients (76 male and 58 female) with STS with an average age of 56.6 years. The tumours involved the upper extremity in 20 patients, lower extremity and trunk in 50 patients each and other areas in 14 patients. The most frequent histological subtypes were liposarcomas (n = 31, 23.5%) and undifferentiated pleomorphic sarcomas (n = 24, 18.2%). Initial treatment was delayed by an average of 9.9 months for all groups. The period of treatment delay for tumours involving the upper extremity was shorter (7.9 months) and these tumours were smaller at initial presentation (57.6 mm) compared to tumours in other locations (p < 0.05). Other factors that were positively associated with treatment delays were a history of diabetes mellitus (p = 0.037) and smoking (p = 0.026). Conclusion: Patients with upper-extremity STS may have the benefit of a relatively better prognosis as they present earlier and with a smaller tumour. In addition, factors, such as diabetes and smoking, which indicate a low interest in health also influenced the delay in the initial treatment. Level of Evidence: Level III (Therapeutic).

Driving to Childhood Cancer Hub Hospitals: A Study on Hospital Accessibility in Japan

Objective:

In 2013, 15 childhood cancer hub hospitals in Japan were designated to provide quality medical treatment and care. The present study assessed hospital accessibility by investigating travel times and distances from patient residences.

Methods:

A total of 37,309 residence/hospital pairs were generated using the addresses of 15 hub hospitals that were designated in 2019 and local government offices in 2014. Using the Google Directions Application Programming Interface (API), travel times and distances were calculated on the assumption that each patient would arrive by driving to the hospitals by 10 am on Wednesday, November 6, 2019. Thus, after identifying the nearest hospital for each residence and deriving adjusted estimated travel times (AETT), the data were summarized according to the regional block using weighted population descriptive statistics for children under 15 years of age in 2015. The cumulative distribution functions of the weighted mean of AETT were also plotted.

Results:

Childhood cancer patients could access the nearest hub hospital by traveling approximately 1.78 hours (AETT, range: 0.1 to 41.8) and 91.86 km (range: 1.0 to 1438.0). Moreover, a total of 94.5% of patients had the nearest hub hospital within their own regional block. The cumulative distribution functions of AETT indicated that many children in three blocks with multiple hub hospitals have shorter travel times and better hospital accessibility than those in other blocks.

Conclusions:

Although feasibility is ultimately dependent on each patient’s condition and situation, child cancer patients on average can likely complete hospital visits from home and return within a single day. However, this is likely not the case for children who live at considerable distances from hub hospitals. We found regional differences in travel times and distances, depending on whether a given block contained multiple hub hospitals.