Financial Distress of Cancer Patients and the Families: Analysis of Individual Consultations Data through Text Mining

This study aimed to clarify financial issues of cancer patients and their families through consultation records. At four sites, 125 reports of individual consultations with regard to employment and finances through financial planner and certified social insurance labor consultant were analyzed using text mining. The mean age of participants was 54.0 ± 10.1 years, and 70 were female (56.0%). The most frequent five words and their co-occurring words were as follows: “month” (104 times; co-occurring words: “leave of absence” and “year”), “injury and sickness allowance” (93 times; co-occurring words: “receive” and “leave of absence”), “current” (72 times; co-occurring words: “receive” and “income”), “work” (68 times; co-occurring words: “contents” and “continue”), and “treatment” (62 times; co-occurring words: “living” and “income”). Our result indicated that participants felt anxious about finances and impact on their life associated with cancer treatment. In addition, cancer patients and their families received advice about timing, ways, and choice of return to work, resigning, and continuing to work, and use of public system including injury and sickness allowance that people can use during their leave of absence from consultants.

The Efficiency of Data Collection Using the Japan Adult Cardiovascular Surgery Database (JACVSD) as a Historical Control in Clinical Trials / 日本心臓血管外科学会雑誌

Recently, the use of databases for clinical trials is being promoted. We used the Japan Adult Cardiovascular Surgery Database (JACVSD) data was used as a historical control in a clinical trial, and we analyzed following : the processes of using data and the efficiency of data collection, available variables for statistical analysis, and query functions for missing and invalid data. We chose available variables of JACVSD data and created rules for merging JACVSD data with interventional group data, in addition to analyzing the data collection processes for clinical trials. Subjects were selected from cases registered in the JACVSD. On statistical analysis, 63% of 76 variables were used ; variables related to the patients' symptoms had to be collected separately. Missing and invalid data were effectively excluded. We could conduct data collection efficiently by using the JACVSD as a historical control for clinical trials. Selecting subjects from the JACVSD could reduce the burden of selecting subjects from hospitals and prevent selection bias.