Independent Ethics Committees and Institutional Review Boards for ClinicalTrial.gov: NCT01072396. (PDF 71 kb

Harry Rossiter (3476834)

Heather Paden (3476825)

Janos Porszasz (558011)

Richard Casaburi (76801)

Robert Cao (3476828)

Susan Blonshine (3476831)

PubMed

Janos Porszasz

Susan Blonshine

Robert Cao

Heather A. Paden

Richard Casaburi

Harry B. Rossiter

Springer - Publisher Connector

Biological quality control for cardiopulmonary exercise testing in multicenter clinical trials

BackgroundPrecision and accuracy assurance in cardiopulmonary exercise testing (CPET) facilitates multicenter clinical trials by maximizing statistical power and minimizing participant risk. Current guidelines recommend quality control that is largely based on precision at individual testing centers (minimizing test-retest variability). The aim of this study was to establish a multicenter biological quality control (BioQC) method that considers both precision and accuracy in CPET.MethodsBioQC testing was 6-min treadmill walking at 20 W and 70 W (below the lactate threshold) with healthy non-smoking laboratory staff (15 centers; ~16 months). Measurements were made twice within the initial 4 weeks and quarterly thereafter. Quality control was based on: 1) within-center precision (coefficient of variation [CV] for oxygen uptake [V̇O2], carbon dioxide output [V̇CO2], and minute ventilation [V̇E] within ±10%); and 2) a criterion that V̇O2 at 20 W and 70 W, and ∆V̇O2/∆WR were each within ±10 % predicted. "Failed" BioQC tests (i.e., those outside the predetermined criterion) prompted troubleshooting and repeated measurements. An additional retrospective analysis, using a composite z-score combining both BioQC precision and accuracy of V̇O2 at 70 W and ∆V̇O2/∆WR, was compared with the other methods.ResultsOf 129 tests (5 to 8 per center), 98 (76%) were accepted by within-center precision alone. Within-center CV was &lt;9%, but between-center CV remained high (9.6 to 12.5%). Only 43 (33%) tests had all V̇O2 measurements within the ±10% predicted criterion. However, a composite z-score of 0.67 identified 67 (52%) non-normal outlying tests, exclusion of which coincided with the minimum CV for CPET variables.ConclusionsStudy-wide BioQC using a composite z-score can increase study-wide precision and accuracy, and optimize the design and conduct of multicenter clinical trials involving CPET.Trial registrationClinicalTrials.gov identifier: NCT01072396; February 19, 2010

Porszasz, Janos

Blonshine, Susan

Cao, Robert

Paden, Heather A

Casaburi, Richard

Rossiter, Harry B

eScholarship - University of California

Biological quality control for cardiopulmonary exercise testing in multicenter clinical trials.

藤井, 淳一

Kyoto University Research Information Repository

Title相対作用素エントロピーをめぐって(作用素不等式とその周辺)Author(s)藤井, 淳一Citation数理解析研究所講究録 (1995), 903: 49-56Issue Date1995-03URL http://hdl.handle.net/2433/59404RightType Departmental Bulletin PaperTextversionpublisherKyoto University– (Jun Ichi Fujii)- Hilbert [17]$S(A|B)$ $A,$ $B$$S(A|B)=A^{1/2}(\log A^{-1/}2BA^{-1/2})A1/2B^{1/}=\eta 2(B^{-1/2}AB-1/2)B^{1/}2$$(\eta(X)=-x\log x)$$S(A|B)=$ s-lim $S(A|B+\epsilon)$ ( )[9] $S(A|B)$[11] :: $\exists c\in \mathbb{R}$ ; $c\leq tB-(\mathrm{l}\circ \mathrm{g}t)A$ $(t>1)$ .$S(A|B)$ $(A, B)$Douglas majorization theorem [5] [15]$S(A|B)$ $[8,12]$ : $R=(A+B)^{1/2}$$\mathrm{k}\mathrm{e}\mathrm{r}X\supset \mathrm{k}\mathrm{e}\mathrm{r}R$ $XR=A1/2$ $X$ –$S(A|B)=RF(X^{*}X)R$ $F(x)=S(x|1-x)=x \log\frac{1-x}{x}$ .$S(A|B)$Uhlmann $x^{t}$ ( )$g_{t}$$S(A|B)=\mathrm{s}- t\downarrow 1\mathrm{i}\mathrm{m}0$$\frac{Ag_{t}B-A}{t}$ ( )[10]903 1995 49-56 49Lebesgue [3] , $A$B-$A=[B]A\equiv$ s-lim $A$ $nB$ (: [2, 6])$narrow\infty$$\mathrm{s}- \mathrm{l}\mathrm{i}\mathrm{m}t$$Ag_{t}B=[B]A$ Uhlmann: $\mathrm{k}\mathrm{e}\mathrm{r}A\supset \mathrm{k}\mathrm{e}\mathrm{r}B$: ran $A^{1/2}\subset$ ran $B^{1/2}$:1. :majorization (1) (2) (3)ran $A^{1/2}\subset$ ran $B^{1/2}$ $\Rightarrow$ $\Rightarrow B$- $\Rightarrow \mathrm{k}\mathrm{e}\mathrm{r}A\supset \mathrm{k}\mathrm{e}\mathrm{r}B$ .:(1) $B=A^{2}$ $S(A|A^{2})=A\log A^{2}-A\log A=A\log A$(2) $A=P_{B}$ $S(P_{B}|B)=PB\log B$(3) $C[0,1]$ 1, $x$ $A,$ $B$ .//Uhlmann [18]– $m_{t}$ $m$$[10,13]$ :$Am_{0}B=A$ , $Am_{1}B=B$ , $m_{1/2}=m$ ,(A $m_{r}B$ ) $m_{t}$ (A $m_{S}B$ ) $=Am_{\langle 1-t)r}+tsB$ $(0\leq r, s, b, \leq 1)$ .$r$-power mean $m^{[r]}(-1\leq$$r\leq 1)$ [7]A $g^{[r]}B=A^{1/2}( \frac{1+(A^{-1/}2BA^{-}1/2)^{r}}{2})^{1/r}A1/2$50A $g_{t}^{[r]_{B}1/2}=A((1-t)+t(A^{-}1/2BA-1/2)^{r)}1/r_{A1/2}$$m^{[1]}=a$ ( ), $m^{[0]}=g$ ( ), $m^{[-1]}=h$ ( )$[B]A$ $B$- [16] $M$$M=\overline{\{y|A1/2\in \mathrm{r}a\mathrm{n}By\}}$$P_{M}$ :. $[B]A=A1/2P_{M}A^{1}/2$$A,$ $B$s-lim $AmtB=Am0B$$t\downarrow 0$– $B[A]$ $\mathrm{s}-\lim_{t}$ $Ag_{t}B=[B]A$:$[B]A= \mathrm{s}-\lim_{t\downarrow 0}A:\frac{1-t}{t}B=\mathrm{s}-\lim_{f\downarrow 0}(1-t)(Ag^{[-1]}B)$ ., $Am_{t}B$ – :2. $1m\mathrm{O}\equiv \mathrm{o}m1=0$s-lim A $m_{t}B=A^{1/21}P_{M}A/2=[B]A$ .$t\downarrow 0$$\mathrm{s}-\lim_{t}$$Am_{t}B=A$ .( ) 1 $m_{t}0=0m_{t}1=0$$F_{t}(x)=x(1m_{t} \frac{1-x}{x})arrow x\chi_{\mathrm{t}^{0},\infty)}(\frac{1-x}{x})=x\chi_{\mathrm{t}^{0,1}})(X)=x\chi[0,1)(x)$.51$P$ $1-Xx*$$F_{t}(x^{*}x)arrow X^{*}X\chi_{[0,1})(x^{*}x)=x^{*}\chi_{[0,1})(XX^{*})X=X^{*}PX$ ,s-lim A $m_{t}B=Rx^{*}PXR=A1/2PA^{1/}2$ .$t\downarrow 0$$F_{t}(x)arrow x$ $(t\downarrow \mathrm{O})$ //$Am\neq B$ $t$ [13],:3. $m_{t}$ $Am_{t}B$ $0<t<1$ .( ) $[0,1]$ $F_{t}(x)=xm_{t}(1-X)$ $F_{t}(1/2)=1/2$ $[0,1/2]$, [1/2, 1] $(0\leq t\uparrow 1)$ $t$ $C[0,1]$$||Am_{t+\epsilon}B-Am_{t}B||\leq||R||||F_{t}+\mathcal{E}^{-F_{t}}||\infty||R||arrow 0$.( )$\varphi_{\epsilon}(_{X})\equiv\frac{F_{t+\epsilon}(x)-Ft(x)}{\hat{\mathrm{c}}}\downarrow\frac{dF_{t}}{dt}(x)$ $(\epsilon\downarrow 0)$ .$x$ Dini $\varphi_{\epsilon}$, $Am_{t}B$ //Uhlmann – $m$ $m_{t}$ $0$derivative solidarity $s_{m}$ :A $s_{m}B= \mathrm{s}-\lim_{t\downarrow 0}\frac{Am_{t}B-A}{t}$ .$s_{m}$ – $m_{t}$ :524 . $m_{t}$ – :$\frac{dAm_{t}B}{dt}=\frac{(Am_{t}B)S_{m}(Amt+.hB)}{h}.\cdot$( ) $\frac{(Am_{t}B)s_{m}(Amt+hB)}{h}=$$\mathrm{s}-\lim_{\epsilon}$$\frac{(Am_{t}B)m\epsilon(Am_{t+}hB)-Am_{t}B}{h_{\mathcal{E}}}$$= \mathrm{s}-\lim_{\epsilon\downarrow 0}\frac{(Am_{\mathrm{t}^{1}-\in})t+\mathcal{E}\mathrm{t}^{t}+h)B)-Am_{t^{B}}}{h_{\mathcal{E}}}$$= \mathrm{s}-\lim_{\in}$$\frac{(Am_{t}+h\xi B)-Am_{t^{B}}}{h\in}=\frac{dAm_{t}B}{dt}$.//$\frac{dAg_{t}B}{dt}=\frac{S(AgtB|Agt+hB)}{h}=$ $\mathrm{u}-\lim_{h\downarrow 0}\frac{S(AgtB|Agt+hB)}{h}$: $(-1, \infty)$$f(x)= \frac{\log(1+x)}{x}$$f(\mathrm{O})=1$ $0$$E_{h}$$f(||E_{h}||)\leq f(E_{h})\leq f(-||E_{h}||)$ $f(E_{h})$ 1$E_{h}$ $E_{h}\geq-1,$$\mathrm{s}_{h}- \mathrm{J}\mathrm{i}\mathrm{m}E_{h}=0$ $\mathrm{S}^{-},1\mathrm{i}\iota \mathrm{r}\mathrm{n}$$F(E_{h}.)=1$ .:5. $A,$ $B$ :$\mathrm{u}-\lim_{h\downarrow 0}\frac{S(Am_{t}B|Am_{t+}hB)}{h}=\mathrm{u}-\lim_{harrow 0}\frac{S(AmtB+\mathcal{E}|Am_{t}+hB+\epsilon)}{h}--\frac{dAm_{t}B}{dt}$ .( ) $f$ $X_{t}=Am_{t}B,$ $E_{h}=X_{t}-1/2.(X_{t+h}-x_{t})x_{t}^{-1}/2$$\frac{S(X_{t}|Xt+h)}{h}=X_{tt}^{1/1/2}2_{\frac{\log X_{t+ht}^{-}Xt1/21/2x^{-}}{h}}x$. .$=X_{tt}^{1/1/2}2 \frac{\log(1+E_{h})}{h}X$$=X_{tt}^{1/1/2}2_{\frac{E_{h}f(E_{h})}{h}}X arrow\frac{dX_{t}}{db}$ (uniformly).53$dX_{t}/dt=d(X_{t}+\epsilon)/dt$ //$S(X_{t}+\epsilon|X_{t+h}+\epsilon)\geq S(X_{t}|X_{t+h})+S(\epsilon|\mathcal{E})=S(X_{t}|X_{t+h})$:5 ,. s-Jim $\underline{S(Am_{t}B|},Am_{t+}hB$) $\leq \mathrm{u}-\lim.=\underline{S(Am_{t}B+\epsilon|Amt+hB+\epsilon)}\underline{dAm_{t}},.B$$h\downarrow 0-11111$ $h$$-\backslash$$\mathrm{u}_{h}^{-}11arrow 0111$ $h$–$dt$$g\geq m$ : $Xs_{m}Y\leq S(X|\mathrm{Y})$$\frac{dAm_{t}B}{dt}=\frac{(Am_{t}B)S_{m}(Amt+hB)}{h}\leq\frac{S(Am_{t}B|Am_{t+}hB)}{h}$//$r$-power mean :$r>0$ $F_{t}^{\{r)}(x)=xm_{t}^{(r)}(1-x)$ $K(h)=(t+h)/t$$F_{t+h}^{\langle r})\leq K(h)F_{t}^{1r)}$ $X_{t}=Am_{t}B$$X_{t+h}=RF_{t+h(}c)R\leq K(h)RF_{t}(C)R=K(h)X_{t}$majorize $\lim_{h\downarrow 0}K(h)=1$$\exists \mathrm{Y}_{h;^{x_{t+h}^{1/}}}2=Y_{h}x_{t}^{1/2},$ $Y_{h}^{*}Y_{h}\leq K(h),$$\mathrm{S}-\lim_{h\downarrow 0}Y^{*}hYh=1_{X}$.$S(x_{t}|X_{t+}h)=^{x_{t}S(|Y_{h}}1*Y_{h})xt=Xt(\log Y_{h}^{*}Yh)X_{t}$ ,$\frac{S(X_{t}|x_{t}+h)}{h}=\frac{X_{i}(\log Y_{h}*Yh)x_{t}}{h}=\frac{X_{i}(\mathrm{Y}_{h}^{*}Y_{h}-1)f(\mathrm{Y}*Yh-h1)Xt}{h}arrow\frac{dX_{t}}{db}(\mathrm{s}\mathrm{t}\mathrm{r}\mathrm{o}\mathrm{n}\mathrm{g}\mathrm{l}\mathrm{y}).//$(cf. [1])$S(A|B)= \mathrm{s}-\lim_{t\downarrow 0}\frac{Ag_{t}B-AatB}{t}+B-A$54$\alpha$-divergence:$D_{\alpha}(A, B)= \frac{4}{1-\alpha^{2}}(Aa_{\mathrm{t}\mathrm{J}+}/2B-Ag\mathrm{t}1+\alpha)/2B)\alpha)$$= \frac{4}{1-\alpha^{2}}(\frac{1-\alpha}{2}A+\frac{1+\alpha}{2}B-Ag\langle 1+\alpha)/2B)$ .$\alpha=0$ 4$D_{1}(A|B) \equiv \mathrm{s}-\lim_{\alpha\uparrow 1}D_{\alpha}(A|B)=-s(B|A)+A-B$$D_{-1}(A|B) \equiv \mathrm{S}-\lim_{\alpha\downarrow-1}D\alpha(A|B)=-s(A|B)+B-A$ .$\alpha$-divergence ,$A,$ $B$ Belavkin-Staszewski$[4,14]$$M$55References[1] –. : , ( 12), 1993.[2] $\mathrm{W}.\mathrm{N}$ .Anderson and $\mathrm{R}.\mathrm{J}$ .Duffin: Series and parallel addition of matrices, J. Math. Anal.Appl., 26 (1969), 576-594.[3] T.Ando: Lebesgue type decomposition of positive operators, Acta Sci. Math., 38(1976),253-260.[4] $\mathrm{V}.\mathrm{P}$.Belavkin and P.Staszewski: $\mathrm{C}^{*}$-algebraic generalization of relative entropy and entropy,Ann. Inst. H. Poincar\’e Sect. A37(1982), 51-58.[5] $\mathrm{R}.\mathrm{G}$ .Douglas: On majorization, factorization and range inclusion of operators in Hilbertspace, Proc. Amer. Math. Soc., 17(1966), 413-416.[6] $\mathrm{P}.\mathrm{A}$ .Fillmore and $\mathrm{J}.\mathrm{P}$.Williams: On operator ranges, Adv. in Math., 7(1971), 254-281.[7] $\mathrm{J}.\mathrm{I}$ .Fujii, F.Kubo and K.Kubo : A parametrization between operator means, Math. $\mathrm{J}$apon.,33 (1988), 201-208.[8] $\mathrm{J}.\mathrm{I}$ .Fujii: On Izumino’s view of operator means, Math. Japon., 33 (1988), 671-675.[9] $\mathrm{J}.\mathrm{I}$ .Fujii and E.Kamei: Relative operator entropy in noncommutative information theory,Math. Japon., 34 (1989), 341-348.[10] $\mathrm{J}.\mathrm{I}$ .Fujii and E.Kamei: Uhlmann’s interpolational method for operator means. Math.Japon., 34 (1989), 541-547.[11] $\mathrm{J}.\mathrm{I}$ .Fujii, M.Fujii and Y.Seo: An extension of the Kubo-Ando theory: Solidarities, Math.Japon., 35 (1990), 387-396.[12] $\mathrm{J}.\mathrm{I}$ .Fujii: Operator means and the relative operator entropy, Operator Theory: Advancesand Applications, Birkh\"auser, 59 (1992), 161-172.[13] $\mathrm{J}.\mathrm{I}$ .Fujii and E.Kamei: Interpolational paths and their derivatives, Math. $\mathrm{J}$apon., 39 (1994),557-560.[14] F.Hiai and D.Petz: The proper formula for relative entropy and its asymptotics in quantumprobability, Preprint.[15] S.Izumino: Quotients of bounded operators, Proc. Amer. Math. Soc., 106(1989), 427-435.[16] H.Kosaki: Remarks on Lebesgue-type decomposition of positive operators, J. Operatortheory, 11 (1984), 137-143.[17] F.Kubo and T.Ando: Means of positive linear operators, Math. Ann., 248 (1980) 205-224.[18] A.Uhlmann: Relative entropy and the $\mathrm{W}\mathrm{i}\mathrm{g}\mathrm{n}\mathrm{e}\Gamma-\mathrm{Y}\mathrm{a}\mathrm{n}\mathrm{a}\mathrm{S}\mathrm{e}$ -Dyson-Lieb concavity in an interpo-lation theory, Commun. Math. Phys., 54 (1977), 22-32.56

相対作用素エントロピーをめぐって(作用素不等式とその周辺)

Background: Precision and accuracy assurance in cardiopulmonary exercise testing (CPET) facilitates multicenter clinical trials by maximizing statistical power and minimizing participant risk. Current guidelines recommend quality control that is largely based on precision at individual testing centers (minimizing test-retest variability). The aim of this study was to establish a multicenter biological quality control (BioQC) method that considers both precision and accuracy in CPET. Methods: BioQC testing was 6-min treadmill walking at 20W and 70W (below the lactate threshold) with healthy non-smoking laboratory staff (15 centers; ~16months). Measurements were made twice within the initial 4weeks and quarterly thereafter. Quality control was based on: 1) within-center precision (coefficient of variation [CV] for oxygen uptake [VO2], carbon dioxide output [VCO2], and minute ventilation [VE] within ±10%); and 2) a criterion that VO2 at 20W and 70W, and VO2/WR were each within ±10% predicted. "Failed" BioQC tests (i.e., those outside the predetermined criterion) prompted troubleshooting and repeated measurements. An additional retrospective analysis, using a composite z-score combining both BioQC precision and accuracy of VO2 at 70W and VO2/WR, was compared with the other methods. Results: Of 129 tests (5 to 8 per center), 98 (76%) were accepted by within-center precision alone. Within-center CV was <9%, but between-center CV remained high (9.6 to 12.5%). Only 43 (33%) tests had all VO2 measurements within the ±10% predicted criterion. However, a composite z-score of 0.67 identified 67 (52%) non-normal outlying tests, exclusion of which coincided with the minimum CV for CPET variables. Conclusions: Study-wide BioQC using a composite z-score can increase study-wide precision and accuracy, and optimize the design and conduct of multicenter clinical trials involving CPET. Trial registration: ClinicalTrials.gov identifier: NCT01072396 ; February 19, 2010

Porszasz, J

Blonshine, S

Cao, R

Paden, HA

Casaburi, R

Rossiter, HB

White Rose Research Online

Crossref

BMC Pulmonary Medicine

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Additional file 1: Table S1. of Biological quality control for cardiopulmonary exercise testing in multicenter clinical trials

https://eprints.whiterose.ac.uk/94471/1/69-Porszasz%20BioQC%20PulmMed%202016.pdf

相対作用素エントロピーをめぐって(作用素不等式とその周辺)

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