Data and cohort construction
In this retrospective cohort study, we performed a record linkage of population-based cancer registry data and administrative data to analyze the relationship between patient mortality and clinical information that is unavailable in cancer registries. Data were obtained from a 5-year period spanning January 2010 to December 2014. The study protocol was approved by the Institutional Review Board of Osaka International Cancer Institute (Approval number: 1707105108).
Cancer registry data were obtained from the Osaka Cancer Registry, a population-based registry that compiles information on cancer diagnoses and outcomes in patients residing in Osaka Prefecture (the third most populous prefecture after Tokyo and Kanagawa). Data include patient sex, age at cancer diagnosis, use or non-use of curative resection and adjuvant chemotherapy for colon cancer, surgical approach (laparoscopic or open), vital status, and dates of death or the last follow-up to determine vital status. Tumor-specific data include primary location, degree of differentiation, date of cancer diagnosis, and Surveillance, Epidemiology, and End Results (SEER) summary stage.(22)
The administrative data used in this study were produced under Japan’s Diagnosis Procedure Combination (DPC) per-diem payment system, which determines insurers’ reimbursements to acute care hospitals for the provision of healthcare services. These data are widely used for research in Japan.(23) DPC data comprise clinical summaries and detailed insurance claims, and include information on comorbidities, preoperative and postoperative activities of daily living (ADL), postoperative complications, and prescribed drugs. The data were obtained from 36 government-designated cancer care hospitals located throughout Osaka Prefecture.
The two data sources were linked at the patient level using each hospital’s patient identification number as a linkage key.(24) This record-linked database encompassed approximately 50% of all newly diagnosed cancer cases in Osaka Prefecture during the study period.
Colon cancer cases were identified using the relevant International Classification of Diseases for Oncology, Third Edition (ICD-O3) topographical codes. Candidate subjects comprised patients aged 18 years or older who had been diagnosed with colon cancer (C18.0, C18.2–C18.8, or C19.9) at any of the 36 cancer care hospitals and had been registered in the Osaka Cancer Registry between January 1, 2010 and December 31, 2014. We focused on patients who received a diagnosis of adenocarcinoma (ICD-O3 morphological codes: 8140, 8211, 8260, 8480, 8490, or 8510) with regional lymph node metastasis according to SEER staging criteria, and had undergone curative resection for colon cancer. Regional lymph node metastasis (T1–T4a, N1–N2, M0) in the SEER staging system was ascertained in stage III (T1–T4, N1–N2, M0) patients according to the TNM classification system (version 7) of the American Joint Committee on Cancer.(25) Patients were excluded from analysis if they had missing vital status data, or had died within 90 days from the cancer diagnosis.
The exposure of interest was the use of adjuvant chemotherapy, which was defined as the administration of chemotherapy within four months after surgical resection that was included in the initial cancer treatment plan. The following seven types of adjuvant chemotherapy were identified in the DPC data for analysis: 5-FU/LV, CAPE, UFT/LV, S-1, FOLFOX, CAPEOX, and SOX. The first three regimens are types of single-agent chemotherapy (monotherapy), and the remaining four regimens are types of double-agent chemotherapy (combined therapy).
The endpoint was overall survival (OS), which was calculated as the number of days from the date of cancer diagnosis until the date of all-cause death, loss to follow-up, or alive through May 2018.
Several demographic and clinical variables were obtained for analysis. These included sex, age at diagnosis (<75 and ≥75 years), and degree of tumor differentiation (well-, moderately, and poorly differentiated). In addition, tumor localization was divided into two anatomical subsites: right colon (ICD-O3 topographical codes: C18.0 and C18.2–C18.5) and left colon (C18.6–C18.8 and C19.9). Body mass index was classified into four categories (<18.5, 18.5–24.9, 25.0–29.9, and ≥30 kg/m2). The Charlson comorbidity index (CCI) was used to measure patients’ comorbidities on admission for radical surgery for colon cancer,(26, 27) and was classified into four categories based on CCI scores (0, 1, 2, or ≥3). The Barthel index was used to measure patients’ ADL on admission and discharge for radical surgery for colon cancer; this index uses a scale from 0 to 100, and was classified into five categories (0-20, 21-60, 61-90, 90-99, 100) for analysis.(28) The following postoperative complications were identified from the relevant data fields in the DPC file using International Classification of Diseases, Tenth Revision codes: surgical site infection (T79.3 or T81.4), peritonitis or peritoneal abscess (K65.x), pancreatic injury (K91.8), ileus (K56.x or K91.3), anastomotic stenosis (T81.8), sepsis (A40.x or A41.x), respiratory complication (pneumonia [J12.x–J18.x], postprocedural respiratory disorder [J95.x], or respiratory failure [J96.x]), pulmonary embolism (I26.x), cardiac event (acute coronary event [I21.x–I24.x] or heart failure [I50.x]), cerebral infarction or hemorrhage (I60.x–I64.x), acute renal failure (N17.x), and urinary tract infection (N10.x, N30.x, or N39.0).(29)
Statistical analyses
The clinical factors and adjuvant chemotherapy regimens for each of the patient age groups (<75 and ≥75 years) were analyzed using descriptive statistics. We examined frequencies for categorical variables and medians with interquartile range (IQR) for continuous variables. Univariate analyses were employed to compare the variables between the two patient age groups, in which categorical variables were compared with Fisher’s exact test and continuous variables were compared with the Mann-Whitney U test.
Survival analysis was performed using the Kaplan-Meier method, and survival estimates were compared using the log-rank test. The effect of adjuvant chemotherapy on OS was analyzed using Cox proportional hazards regression models for all-cause mortality with inverse probability weighting based on propensity scores to adjust for differences between the postoperative treatment groups (surgery with adjuvant chemotherapy and surgery alone).(30) In order to determine the inverse probability of treatment weights, each patient’s propensity score was calculated using logistic regression to estimate the probability of receiving adjuvant chemotherapy conditional to his/her characteristics: sex, age at diagnosis, degree of tumor differentiation, radical surgery procedure, tumor location, body mass index, preoperative and postoperative Barthel index, CCI, and postoperative complications. We then assigned patients who underwent postoperative adjuvant chemotherapy a weight of 1÷(propensity score) and those who underwent surgery alone a weight of 1÷(1−propensity score). We assessed covariate balance using absolute standardized differences; a difference of 10% or less was considered to indicate a well-balanced result.(31) Adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated for each patient age group. Missing data were imputed using the multiple imputation method.(32) We also estimated adjusted HRs using complete data (without missing data imputation) as a sensitivity analysis.
All significance tests were 2-sided and P values <0.05 were considered to be statistically significant. Statistical analyses were performed using STATA version 15.1 software (STATA Corporation, College Station, TX, USA).
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.