| Literature DB >> 27099666 |
Yousef Veisani1, Ali Delpisheh2.
Abstract
AIM: In this study, we aimed to estimate one- to five-year survival rates in Iranian patients with gastric cancer (GC). In addition, we preformed subgroup analyses and meta-regression to explore possible sources of heterogeneity between studies.Entities:
Keywords: Gastric cancer; Heterogeneityndrial; Meta-analysis; Survival rate; Systematic review
Year: 2016 PMID: 27099666 PMCID: PMC4833845
Source DB: PubMed Journal: Gastroenterol Hepatol Bed Bench ISSN: 2008-2258
Feature and characteristic studies included in study
| Ref. | First Author | Years of flow | No. of Patients | Data source | Analysis | Survival Rate (%) | Quality* | ||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1-Year | 2-Year | 3-Year | 4-Year | 5-Year | |||||||
| ( | Biglarian A | 2002-2007, | 436 | Hospital records | Cox proportional hazards | 78 | 53 | 41 | 32 | 17 | High |
| ( | Mehrabian AA | 2001-2006, National | 19537 | Iran Cancer Registration | Life time table | 49 | 29 | 23 | 23 | 15 | High |
| ( | Soroush A | 2008-2010, | 98 | Hospital records | Kaplan–Meier method and Cox proportional hazard models | 60 | 31 | High | |||
| ( | Zare A | 1995-1999, | 330 | Iran Cancer Institute | Cox proportional hazards model | 66 | 42 | 31 | 26 | 21 | High |
| ( | Baghestani AR | 2003-2008, Tehran | 178 | Hospital records | Bayesian Weibull and Exponential models | 80 | 52 | 35 | High | ||
| ( | Moghimi-Dehkordi B | 2001-2006, | 746 | Cancer Registry | life-table method and Wilcoxon (Gehan) test | 73 | 50 | 40 | 33 | 29 | High |
| ( | Samadi F | 2000-2004, Ardabil | 279 | Hospital records | Kaplan–Meier method and Cox proportional hazard models | 41 | 8 | High | |||
| ( | Noorkojuri H | 2003-2008, | 216 | Tehran Cancer Registry | Cox proportional hazards and smoothing methods | 80 | 56 | 40 | 35 | 30 | High |
| ( | Yazdani-Charati J | 2007-2010, Sari | 190 | Hospital records | Kaplan-Meier | 45 | 26 | 8 | High | ||
| ( | Ghadimi Gh | 1990-199, | 484 | Cancer Registration Center | Weibull, Log-normal, and the Log-logistic model | 24 | 16 | 15 | High | ||
| ( | Maroufizadeh S | 2003-1008, | 213 | Cancer Registration Center | Cox and Additive hazards models | 79 | 35 | 14 | High | ||
| ( | Bashash M, | 2004, | 261 | population-based cancer registries | Life-tables | 21 | High | ||||
| ( | Movahedi M, | 2001-2005, | 3189 | national cancer registry | Kaplan-Meier | 48 | 27 | 19 | 16 | 13 | High |
| ( | Veisani Y, | 2006-2011, | 239 | Hospital records | Kaplan-Meier | 41 | 17 | 13 | 10 | 6 | High |
| ( | Atoof F, | 1995-2004, | 330 | Hospital records | Kaplan-Meier and Weibull Cure Models | 32 | 20 | Medium | |||
| ( | Roshanaei Gh, | 2003 – 2007, | 400 | Hospital records | Cox proportional hazards | 74 | 54 | 31 | 26 | 23 | Medium |
| ( | Moghimi-Dehkordi B, | 2001-2005, | 442 | Cancer Registration Center | Kaplan–Meier and Cox proportional hazard models | 54 | 30 | 24 | 18 | 16 | Medium |
| ( | Barfei F, | 2007-2008, | 99 | Hospital records | Kaplan–Meier and Cox proportional hazard models | 59 | 40 | 18 | Low | ||
| ( | Kashani H, | 1995-1999, | 330 | Hospital records | Kaplan–Meier and Cox proportional hazard models | 62 | 41 | 31 | 24 | 20 | Medium |
| ( | Baeradeh NA, | 2006-2010, | 136 | Hospital records | Kaplan–Meier and Cox proportional hazard models | 61 | 45 | 31 | 26 | 25 | Medium |
| ( | Zeraati H, | 1995-1999, | 129 | Hospital records | A non-homogenous semi-Markovian stochastic process | 67 | 31 | 19 | Medium | ||
| ( | Ghorbani S, | 2007-2012, | 430 | Cancer Registration Center | Kaplan - Meier and | 64 | 44 | 34 | 28 | 19 | Medium |
| ( | Roshanaei Gh, | 2003-2007, | 262 | Hospital records | Kaplan–Meier and Cox proportional hazard models | 81 | 45 | 30 | Low | ||
| ( | Roshanaei Gh, | 2003-2007, | 93 | Hospital records | Kaplan–Meier models | 42 | 19 | 13 | Medium | ||
| ( | Larizadeh MH,2013 | 2003-2011-Kerman | 82 | Hospital records | Kaplan-Meier methods | 53 | 22 | Low | |||
| ( | Gohari MR, | 2002-2007, | 232 | Hospital records | Kaplan-Meier methods | 77 | 26 | Low | |||
Figure 1Flow diagram shows different steps involved in searching for relevant publications (2005–2015
Subcategories analysis of one to five survival rates by quality and data source
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|---|---|---|---|---|---|---|---|---|
| 1-Year | 2-Year | 3-Year | 4-Year | 5-Year | I2 (%) | P value | ||
| Quality | High | 51(50-51) | 30(29-30) | 23(22-23) | 22(22-23) | 15(14-15) | 98.8 | <0.0001 |
| Medium | 63(61-65) | 42(39-44) | 29(28-31) | 24(22-26) | 19(18-21) | 89.6 | <0.0001 | |
| Low | 77(73-80) | - | 38(34-41) | 22(13-31) | 26(21-30) | 87.5 | <0.0001 | |
| Data Source | Hospital records | 67(65-68) | 41(38-43) | 27(26-29) | 22(20-24) | 16(14-17) | 96.7 | <0.0001 |
| Cancer registry center | 50(49-51) | 30(29-30) | 23(23-24) | 22(22-23) | 15(15-16) | 97.7 | <0.0001 | |
| Overall survival rate | 52(52-53) | 31(30-31) | 24(23-24) | 22(22-23) | 15(15-16) | 95.6 | <0.0001 | |
Figure 4Meta-regression plots of change in one and five survival rate according to changes in continuous study moderator’s year
Figure 3Meta-analysis of the five year survival rate by different data source (Hospital Records and Cancer Registry Centers)