| Literature DB >> 35033080 |
Baibei Li1, Huachu Deng2, Ziyan Zhou3, Bo Tang4.
Abstract
BACKGROUND: In recent years, the Fibrinogen to pre-albumin ratio (FPR) has been reported in many studies to be significantly associated with the prognosis of various cancers. This systematic review and meta-analysis aimed to investigate the prognostic value of FPR in malignant tumors of the digestive system based on available evidence.Entities:
Keywords: Digestive cancers; Fibrinogen to pre-albumin ratio; Prognosis
Year: 2022 PMID: 35033080 PMCID: PMC8760749 DOI: 10.1186/s12935-022-02445-w
Source DB: PubMed Journal: Cancer Cell Int ISSN: 1475-2867 Impact factor: 5.722
Fig. 1The flow chart of the literature selection
The characteristics of included studies
| Study | Year | Country | Cancer site | Design type | Sample | Gender ratio | Treatment | Outcome | Optimal cut-off for FPR | Follow-up |
|---|---|---|---|---|---|---|---|---|---|---|
| Liqun Zhang et al | 2019 | China | CRC | Retrospective | 71 | 44/27 | chemotherapy | PFS | 18.49 by ROC | Median 6.67 (1.86–27.17) |
| Jing Zhang et al | 2017 | China | GC | Retrospective | 360 | 261/99 | Surgical resection | OS | 12.1 by X-tile | More than 36 |
| Fan Sun et al | 2018 | China | CRC | Prospective | 555 | 350/205 | Surgical resection | OS | 18.3 by X-tile | More than 36 |
| Jinghui Du et al | 2019 | China | GBC | Retrospective | 220 | 122/98 | chemotherapy | OS | 31.84 by X-tile | More than 36 |
| Lei Zhang et al | 2018 | China | HCC | Prospective | 230 | 193/37 | Surgical resection | RFS,OS | 15.6 by X-tile | More than 36 |
| Shuli Tang et al | 2020 | China | GC | Prospective | 273 | 197/76 | Surgical resection | OS | 0.0145 by ROC | More than 60 |
| Jifeng Feng et al | 2020 | China | ESCC | Retrospective | 372 | 327/45 | Surgical resection | CSS,OS | 0.014 by ROC | More than 60 |
| Yucui Liao et al | 2021 | China | CMA | Retrospective | 42 | 22/20 | chemotherapy | PFS | 26.2 by X-tile | More than 36 |
| Hailun Xie et al | 2021 | China | CRC | Retrospective | 584 | 363/221 | Surgical resection | complication, DFS, OS | 23.1 by X-tile | More than 60 |
| Hanliang Zhou et al | 2020 | China | CRC | Prospective | 212 | 133/79 | Surgical resection | OS | 18.0 by X-tile | More than 36 |
| Qinggen Chen et al | 2019 | China | CRC | Prospective | 77 | NA | chemotherapy | OS | 22.8 by X-tile | More than 36 |
| Qinggen Chen et al | 2019 | China | CRC | Prospective | 430 | NA | mixed | OS | 22.8 by X-tile | More than 36 |
| Houqun Ying et al | 2021 | China | CRC | Prospective | 1014 | 622/392 | Surgical resection | RFS | 18.3 by X-tile | More than 36 |
| Houqun Ying et al | 2021 | China | CRC | Prospective | 519 | 348/171 | Surgical resection | RFS | 18.3 by X-tile | More than 36 |
| Yucui Liao et al | 2021 | China | CRC | Retrospective | 157 | 91/66 | Surgical resection | RFS | 19.5 by X-tile | More than 36 |
Fig. 2Forest plot for the association between FPR and overall survival
Subgroup Meta-analysis of FPR and OS
| Subgroup | No. of cohorts | No. of patients | Pooled HR (95% CI) | P | Heterogeneity | |
|---|---|---|---|---|---|---|
| Altogether | 10 | 3313 | 1.88(1.53,2.32) | < 0.001 | 50.8 | 0.032 |
| Publishing time | ||||||
| < 2020 | 6 | 1872 | 2.10 (1.67,2.64) | < 0.001 | 25.9 | 0.24 |
| ≥ 2020 | 4 | 1441 | 1.61 (1.25,2.09) | < 0.001 | 53.0 | 0.095 |
| Sample capacity | ||||||
| < 330 | 5 | 1012 | 2.39 (1.55,3.70) | < 0.001 | 60.9 | 0.037 |
| ≥ 330 | 5 | 2301 | 1.57 (1.35,1.83) | < 0.001 | 14.3 | 0.323 |
| Methods for choosing FPR cut-off value | ||||||
| ROC | 2 | 645 | 1.47(1.21,1.78) | < 0.001 | 0.0 | 0.635 |
| X-tile | 8 | 2668 | 2.11(1.61,2.77) | < 0.001 | 50.8 | 0.047 |
| Cut-off value | ||||||
| < 18 | 4 | 1235 | 1.96 (1.34,2.89) | 0.001 | 69.8 | 0.019 |
| ≥ 18 | 6 | 2078 | 1.75(1.44,2.12) | < 0.001 | 39.0 | 0.146 |
| Study designed type | ||||||
| Retrospective | 4 | 1536 | 1.50 (1.28,1.76) | < 0.001 | 2.3 | 0.381 |
| Prospective | 6 | 1777 | 2.32 (1.68,3.19) | < 0.001 | 43.6 | 0.115 |
| Treatment option | ||||||
| Surgical resection | 7 | 2586 | 1.92 (1.48,2.48) | < 0.001 | 62.8 | 0.013 |
| Others | 3 | 727 | 1.80 (1.29,2.52) | 0.001 | 3.0 | 0.357 |
| Cancer site | ||||||
| GC | 2 | 633 | 1.83(1.33,2.51) | < 0.001 | 20.8 | 0.261 |
| CRC | 5 | 1858 | 2.00(1.42,2.81) | < 0.001 | 49.5 | 0.095 |
| GBC | 1 | 220 | 1.57(1.00,2.46) | 0.049 | NA | NA |
| HCC | 1 | 230 | 4.16(2.06,8.39) | < 0.001 | NA | NA |
| ESCC | 1 | 372 | 1.43(1.15,1.78) | 0.002 | NA | NA |
Fig. 3Sensitivity analysis for the association between FPR and OS. OS: overall survival
Fig. 4Plots for publication bias test in meta-analysis for overall survival. a Begg’s funnel plot; b Egger’s publication bias plot; c The trim-and-fill methods;
Fig. 5Forest plot for the association between FPR and recurrence-free survival
Subgroup Meta-analysis of FPR and RFS
| Subgroup | No.of cohorts | No. of patients | Pooled HR (95% CI) | P | Heterogeneity | |
|---|---|---|---|---|---|---|
| Altogether | 4 | 1920 | 2.29(1.91,2.76) | < 0.001 | 35.3 | 0.201 |
| Publishing time | ||||||
| < 2021 | 1 | 230 | 1.77(1.04,2.99) | 0.034 | NA | NA |
| ≥ 2021 | 3 | 1690 | 2.32(1.73,3.11) | < 0.001 | 43.6 | 0.170 |
| Sample capacity | ||||||
| < 480 | 2 | 387 | 1.94(1.26,2.99) | 0.002 | 0.0 | 0.534 |
| ≥ 480 | 2 | 1533 | 2.38(1.94,2.92) | < 0.001 | 71.8 | 0.060 |
| Study designed type | ||||||
| Retrospective | 1 | 157 | 2.36(1.12,4.99) | 0.025 | NA | NA |
| Prospective | 3 | 1763 | 2.17(1.59,2.97) | < 0.001 | 56.8 | 0.099 |
| Cancer site | ||||||
| HCC | 1 | 230 | 1.77(1.04,2.99) | 0.034 | NA | NA |
| CRC | 3 | 1690 | 2.32(1.73,3.11) | < 0.001 | 43.6 | 0.170 |
Fig. 6Sensitivity analysis for the association between FPR and RFS. RFS: recurrence-free survival
Fig. 7Plots for publication bias test in meta-analysis for recurrence-free survival. a Begg’s funnel plot; b Egger’s publication bias plot
Fig. 8Forest plot for the association between FPR and progression-free survival (a)/ complication (b)/ disease-free survival (c) / cancer-specific survival (d)