Table 1.
Characteristics of 101 model developments.
| Model developments (n = 101) | |
|---|---|
| Study characteristics | |
| Publication year | |
| Before 2000 | 3 |
| 2001–2010 | 7 |
| 2011–2018 | 91 |
| Study location | |
| East Asia (China/Japan/Korea) | 76 |
| Non-Asian | 25 |
| Data source | |
| Clinical data/retrospective cohort | 91 |
| Prospective cohort | 7 |
| Randomized controlled trial | 3 |
| Patient characteristics | |
| Male% (4/101 missing) | 67.6 (30.9, 80.3)a |
| Age (5/101 missing) | |
| Median (min, max) of mean | 60.0 (51.0, 70.0)a |
| Tumor TNM stage | |
| All | 46 |
| I–III | 36 |
| IV | 17 |
| No information | 2 |
| Gastrectomy | |
| No restriction | 28 |
| Only patients with gastrectomy | 71 |
| Only patients without gastrectomy | 2 |
| Model development | |
| Sample size (training set) (14/101 missing) | 360 (29, 15320)a |
| Number of events | 193 (14, 9560)a |
| Event per variable (18/101 missing) | 25.1 (0.2, 1481.3)a |
| Length of follow-up (month) (53/101 missing) | 44.0 (6.7, 111.6)a |
| Start of outcome follow-up | |
| From diagnosis | 3 |
| From surgery | 49 |
| From other time pointsb | 15 |
| Unclear | 34 |
| Candidate selection methods | |
| Prespecification | 30 |
| Univariable analysis | 63 |
| Prespecification + univariable analysis | 5 |
| Unclear | 3 |
| Statistical model | |
| Cox proportional hazard regression | 90 |
| Othersc | 11 |
| Final predictor selection | |
| Full model | 10 |
| Stepwise (including forward and backward) | 68 |
| Unclear | 23 |
| Statistical assumptions ever checked | 9 |
| Number of final predictors | 5 (2, 53)a |
| Formats of presentations | |
| Score | 35 |
| Nomogram | 47 |
| Equation | 9 |
| Others (decision tree and neural network) | 4 |
| No | 6 |
| Predictive performance | |
| Discrimination | |
| AUC/c statistic | 67 |
| Others | 1 |
| No | 33 |
| Calibration | |
| Calibration plot | 45 |
| Hosmer–Lemeshow test | 3 |
| No | 55 |
| Model validation | |
| Internal | 30 |
| External | 21 |
| No | 54 |
aMedian (min, max). bInitiation of chemotherapy (n = 10), metastasis (n = 3), and randomization (n = 2). cCART, Cox Lasso, discrimination analysis, Weibull model, neural network, and logistic model. AUC: area under curve.