Background
Methods
Inclusion and exclusion criteria
Literature review
Data extraction
Statistical analysis
Results
Selection procedure
Study characteristics
Study | Year | NOS | Journal | Region | Total number | TET2m | Median age | Detecting method | Data type | Therapy regimen | Cohort type |
---|---|---|---|---|---|---|---|---|---|---|---|
Wahab | 2009 | 7 | Blood | America | 91 | 11 | 65 | Unknown | Calculated from K-M curves | Unknown | AML |
Nibourel | 2010 | 6 | Blood | France | 111 | 19 | 43 | Direct sequencing | Calculated from K-M curves | Anthracycline-cytosine arabinoside induction treatment followed by HDAC consolidation or allo-HSCT | AML |
Metzeler | 2011 | 9 | Journal of Clinical Oncology | America | 418 | 95 | > 60 | Direct sequencing | Calculated from K-M curves | Standard intensive therapy | CN-AML |
Kosmider | 2011 | 7 | Haematologica | France | 247 | 49 | 66 | Direct sequencing | Unitivariate or calculated from K-M curves | Intensive chemotherapy with anthracycline-cytarabine | s-AML |
Chou | 2011 | 7 | Blood | China | 486 | 64 | 51.5 | Unknown | Multivariate and calculated from K-M curves | Standard intensive therapy or palliativecare or low-dose chemotherapy | AML |
Patel | 2012 | 8 | The New England Journal of Medicine | America | 391 | 33 | < 60 | Direct sequencing | Calculated from K-M curves | Induction therapy with high or standard dose of DNR | AML |
Weissmann | 2012 | 7 | Leukemia | Germany | 318 | 87 | 66.4 | Next-generation sequencing | Calculated from K-M curves | Unknown | AML |
Gaidzik | 2012 | 8 | Journal of Clinical Oncology | Germany | 783 | 60 | < 60 | Direct sequencing | Calculated from K-M curves | Double induction therapy | AML |
Renneville | 2014 | 6 | Oncotarget | France | 139 | 19 | 62 | Direct sequencing | Univariate | Standard front-line chemotherapy with or without low-dose gemtuzumab ozogamicin | CN-AML |
Damm | 2014 | 8 | Genes Chromosomes and Cancer | France and Germany | 215 | 13 | < 60 | Direct sequencing | multivariate | Intensive double induction and consolidation therapy | CN-AML |
Tian | 2014 | 7 | International Journal of Hematology | Asia | 373 | 60 | 45 | Direct sequencing | Calculated from K-M curves | Standard induction therapy followed by consolidation of HDAC or allo-HSCT | CN-AML |
S.Ohgami | 2015 | 7 | Modern Pathology | America | 93 | 6 | 55 | Next-generation sequencing | Muitivariate | Standard induction therapy with cytarabine and danorubicin or idarubicin | AML |
Ahn | 2015 | 9 | Haematologica | Multiple region | 407 | 54 | 52 | Direct sequencing | Muitivariate | Standard induction therapy | CN-AML |
Kao | 2015 | 8 | Oncotarget | China | 98 | 18 | 55 | Direct sequencing | Calculated from K-M curves | Standard intensive therapy with daunomycin and cytarabine | AML with MLL-PTD |
Cher | 2016 | 8 | Blood Cancer Journal | China | 96 | 8 | 41 | Next-generation sequencing | Multivariate and univariate | Induction chemotherapy comprising cytarabine and daunorubicin with consolidation therapy comprising HDAC or allo-HSCT | CBF-AML |
Lin | 2016 | 9 | Cancer Medicine | China | 112 | 12 | 42.6 | Next-generation sequencing | Multivariate | Standard therapy with or without allo-HSCT | AML |
Prognosis of TET2 mutation in AML
Variables | Number of studies, heterogeneity I2%, p | Pooled HRs(95% CI), P value | Interaction(p) | |
---|---|---|---|---|
Year | 2016 | 1 | 3.430[1.479–7.955], P = 0.004 | 0.096 |
2015 | 3(74.8), P = 0.019 | 1.320[0.911–1.913], P = 0.142 | ||
2014 | 1 | 0.800[0.327–1.955], P = 0.624 | ||
2012 | 2(1.7), P = 0.313 | 1.613[1.217–2.138], P = 0.001 | ||
2011 | 1 | 1.320[0.982–1.774], P = 0.066 | ||
2010 | 1 | 3.970[1.140–13.826], P = 0.030 | ||
Data type | Multivariate | 3(76.4), P = 0.014 | 1.284[0.891–1.850], P = 0.181 | 0.110 |
Calculated from K-M curves | 5(26.2), P = 0.247 | 1.473[1.209–1.794], P < 0.001 | ||
univariate | 1 | 3.430[1.479–7.955], P = 0.004 | ||
Region | America | 2(83.0), P = 0.015 | 1.479[1.117–1.959], P = 0.006 | 0.413 |
Europe | 4(44.1), P = 0.147 | 1.580[1.215–2.055], P = 0.001 | ||
Asia | 2(76.4), P = 0.040 | 1.934[1.020–3.667], P = 0.043 | ||
other | 1 | 1.076[0.688–1.682], P = 0.748 | ||
Cohort | AML | 2(79.4), P = 0.028 | 1.669[1.189–2.344], P = 0.003 | 0.444 |
CN-AML | 5(47.5), P = 0.106 | 1.377[1.120–1.692], P = 0.002 | ||
Others | 2(76.4), P = 0.040 | 1.934[1.020–3.667], P = 0.043 | ||
Detection methods | Direct sequencing | 6(13.1), P = 0.331 | 1.283[1.058–1.556], P = 0.011 | 0.002 |
Next-generation sequencing | 3(38.3), P = 0.198 | 2.418[1.691–3.459], P < 0.001 |