Technical Description
1. Data Source
Data were obtained from the Cancer Public Library Database (CPLD), established under the
Korean Clinical Data Utilization Network for Research Excellence (K-CURE) project.
The CPLD integrates four nationwide population-based databases:
- Korea National Cancer Incidence Database (KNCI DB)
- Cause-of-death data from Statistics Korea
- National Health Insurance Service (NHIS)
- Health Insurance Review & Assessment Service (HIRA)
The database encompasses 96.7% of all cancer incidence cases in Korea, with an estimated
completeness of 98.3% (as of 2020).
2. Patient Selection
Primary stomach cancer patients diagnosed between 2012 and 2020 were identified from the CPLD
(initial pool: n = 248,501). The following exclusion criteria were applied:
- Unknown or duplicated SEER stage (n = 12,292)
- Death Certificate Only cases or diagnosis date errors (n = 9)
- Age 30 or younger at diagnosis (n = 681)
- Diagnosed in 2012–2013 (n = 55,057; excluded to ensure sufficient follow-up)
The final analytic cohort comprised 180,462 patients diagnosed between 2014 and 2020,
with follow-up through December 31, 2021 (maximum follow-up: ~8 years).
3. Input Variables
Base Variables
| Variable |
Categories / Range |
| Age at diagnosis |
Continuous, 30–85 years |
| Sex |
Male / Female |
| SEER Stage |
Localized / Regional / Distant / Unknown |
| Tumor Location |
Upper / Middle / Lower / Overlapped / Unknown |
| Comorbidity |
None / Mild / Moderate / Severe
Based on 13 conditions (Charlson Comorbidity Index adapted for gastric cancer):
myocardial infarction, congestive heart failure, cerebrovascular disease, dementia, diabetes,
liver disease, paraplegia, chronic pulmonary disease, renal disease, rheumatologic disease,
peptic ulcer disease, peripheral vascular disease, mild/severe liver disease.
Weights were derived from Cox regression on other-cause mortality in this cohort.
|
Health & Lifestyle Variables (optional)
| Variable |
Categories |
| BMI |
Underweight (<20) / Normal (20–24) / Pre-obese (25–29) / Obese (≥30) |
| Metabolic Syndrome |
Yes / No
Defined as ≥3 of: abdominal obesity, high blood pressure,
elevated triglycerides, low HDL, elevated fasting glucose.
|
| Smoking |
Never / Ex-smoker / Current smoker |
| Drinking |
Non-drinker / Low-risk / High-risk
Classified by daily alcohol intake (sex-specific WHO thresholds).
|
| Physical Activity |
None / Low / High
Based on weekly MET-minutes (IPAQ protocol).
|
Treatment Variables (optional)
| Variable |
Categories |
| Initial Surgery |
Endoscopic / Subtotal Gastrectomy / Total Gastrectomy / Others / None |
| Chemotherapy |
Yes / No |
| Radiotherapy |
Yes / No |
4. Statistical Models
Overall Survival (OS) — Cox Proportional Hazards
All-cause mortality is modelled using the Cox proportional hazards model.
Every patient who remains alive at end of follow-up is censored.
$$S(t\mid x) = e^{-H_0(t)\, e^{\beta x}}$$
where $H_0(t)$ is the baseline cumulative hazard and $\beta x$ is the linear predictor.
Cancer-Specific Survival (CSS) — Cause-Specific Hazard
A second Cox model is fitted with gastric cancer death (GCD) as the sole event;
deaths from other causes are censored alongside survivors.
This isolates the hazard attributable to gastric cancer under the assumption of
independent competing risks.
$$\lambda_{cs}(t) = \lim_{\Delta t \to 0} \frac{P(t \le T < t+\Delta t,\; D=\text{GCD} \mid T \ge t)}{\Delta t}$$
Competing Risks — Fine-Gray Subdistribution Hazard
The cumulative incidence of each cause of death is estimated via the Fine-Gray model,
which keeps patients who experienced a competing event in the risk set.
The outcome variable (crisk) is coded as:
- 0 — Alive / censored
- 1 — Gastric cancer death (GCD)
- 2 — Other-cause death (OCD)
Separate models are fitted for GCD (failcode = 1) and OCD (failcode = 2).
$$\lambda_{sd}(t) = \lim_{\Delta t \to 0} \frac{P(t \le T < t+\Delta t,\; D=k \mid T \ge t \text{ or } (T < t \text{ and } D \ne k))}{\Delta t}$$
$$F_k(t\mid x) = 1 - e^{-\Lambda_{sd,k}(t)\, e^{\gamma_k x}}$$
Derived Outcomes
Restricted Mean Survival Time (RMST) — expected survival time up to horizon $\tau$:
$$\text{RMST}(\tau) = \int_0^{\tau} S(t)\, dt$$
Conditional Survival (CS) — probability of surviving an additional $t$ years
given survival to landmark time $\tau$:
$$CS(t \mid \tau) = \frac{S(\tau + t)}{S(\tau)}$$
