| Project/Area Number |
16K12403
|
|---|
| Research Category |
Grant-in-Aid for Challenging Exploratory Research
|
| Allocation Type | Multi-year Fund |
|---|
| Research Field |
Statistical science
|
|---|
| Research Institution | Osaka University (2017-2018)
Kurume University (2016) |
|---|
Principal Investigator |
|
|---|
| Project Period (FY) |
2016-04-01 – 2019-03-31
|
| Project Status |
Completed (Fiscal Year 2018)
|
| Budget Amount *help |
¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Fiscal Year 2018: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2017: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2016: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
|
|---|
| Keywords | メタアナリシス / 診断法研究 / 予後因子研究 / 公表バイアス / 感度解析 / ROC曲線 / 生存時間解析 / 多重代入法 / 時間依存性ROC曲線 |
|---|
| Outline of Final Research Achievements |
No statistical methods were available to quantify magnitude of publication bias on the summary receiver operating characteristic (ROC) curve in meta-analysis of diagnosis studies. In this project, we proposed a sensitivity analysis method for the summary ROC curve, which is the first method to address the issue, in Hattori and Zhou (2016). We are extending this method to survival outcomes. We also developed methods to estimate time-dependent predictive-value curves and reported in Hattori and Zhou (2017). Furthermore, we developed a method to estimate the concordance-index for survival outcomes based on meta-analysis of information reported in literatures. We are preparing for a paper reporting this method to submit to a statistical journal. The achievement enables us to evaluate relationship between a biomarker and a survival outcome more objectively accounging for potential influence of publication bias.
|
| Academic Significance and Societal Importance of the Research Achievements |
個別化医療への期待より、バイオマーカーと生存時間の関連を統計的に評価することが重要となる。我々の研究により関連を評価する上で有用な指標である時間依存性予測値直線、C-indexなどを、先行研究で報告された情報のメタアナリシスにより効率的に推定することが可能となった。また、メタアナリシスを行う際の大きな問題である公表バイアスの影響を評価する方法を開発した。バイオマーカー研究のメタアナリシスにおいては、これまで公表バイアスの影響を評価する方法は皆無であったが、より客観的な評価が可能となった。
|
