The impact of additive or substitutive clinical study design on the negotiated reimbursement for oncology pharmaceuticals after early benefit assessment in Germany

Dintsios, C. M.; Beinhauer, I.

doi:10.1186/s13561-020-00263-2

Table 4 Regression models with transformed and untransformed variables in ascending order of adjusted R-squared

From: The impact of additive or substitutive clinical study design on the negotiated reimbursement for oncology pharmaceuticals after early benefit assessment in Germany

Independent Variable	Coefficient	SE	95% CI	t statistic	P value	R²	adj R²
Additive premiums
(1) Basis regression model using all variables untransformed, and additive premiums as the dependent variable
EU Prices	1.3141259	1.00407225	−1.1427504 – 3.77100219	1.30879616	0.23849493	0.654	0.309
Comparable drugs	−0.1535998	0.23822837	−0.7365236 – 0.42932406	− 0.6447585	0.54293375
Added benefit	9034.29827	10,716.7639	−17,188.678 – 35,257.275	0.84300618	0.4315413
AnTC ACT	−0.0486107	0.28074618	−0.7355719 – 0.63835042	− 0.1731484	0.86822835
Study design dichotomized	7356.39568	15,843.3671	−31,410.927 – 46,123.7184	0.46432022	0.65878822
Target population	−1.6576633	1.20885101	−4.6156151 – 1.30028857	−1.3712718	0.21936371
Constant	52,107.00377	20,198.79989	2682.320947–101,531.6866	2.579707906	0.04178586*
(2) Basis regression model using all variables untransformed, and log additive premiums as the dependent variable
EU Prices	0.00001931	0.00001709	−0.00002252 – 0.00006114	1.12939086	0.30185338	0.705	0.410
Comparable drugs	−0.00000257	0.00000406	−0.00001249 – 0.00000736	−0.63303948	0.55005850
Added benefit	0.19608572	0.18245474	−0.25036495 – 0.64253639	1.07470883	0.32381185
AnTC ACT	−0.00000076	0.00000478	−0.00001245 –0.00001094	−0.15849576	0.87926624
Study design dichotomized	0.07529218	0.26973604	−0.58472812 – 0.73531249	0.27913283	0.78951472
Target population	−0.00003937	0.00002058	−0.00008973 – 0.00001099	−1.91280535	0.10430143
Constant	10.84596964	0.34388803	10.00450596–11.68743333	31.53924778	0.00000007*
*(3) Basis regression model with interaction AnTC ACTTarget population, and log additive premiums as the dependent variable**
EU Prices	0.00002490	0.00001697	−0.00001871 – 0.00006852	1.46787027	0.20206636	0.775	0.460
Comparable drugs	−0.00000580	0.00000467	−0.00001781 – 0.00000620	−1.24238121	0.26918568
Added benefit	0.04432483	0.21293062	−0.50303075 – 0.59168041	0.20816559	0.84331349
AnTC ACT	−0.00000367	0.00000514	−0.00001688 – 0.00000954	− 0.71446967	0.50689617
Target population	−0.00013334	0.00007798	−0.00033380 – 0.00006712	−1.70982331	0.14799077
AnTC ACT*Tar. pop	0.00000000	0.00000000	0.00000000–0.00000001	1.24538235	0.26817087
Study design dichotomized	−0.04186251	0.27475003	−0.74812996 – 0.66440493	− 0.15236582	0.88485596
Constant	11.71190494	0.76927118	9.73443041–13.68937947	15.22467656	0.00002217*
(4) Bivariate regression model using statistical significant variables, and additive premiums as the dependent variable
EU-prices	1.00815416	0.49637946	−0.09784821 – 2.11415654	2.031015043	0.069686298	0.554	0.465
Target population	−1.80975847	0.78477917	−3.55835544 – −0.06116149	−2.306073507	0.043799202*
Constant	61,129.98695	7879.338538	43,573.72662788–78,686.24727887	7.7582638	0.00001539*
(5) Bivariate regression model using statistical significant variables, and log additive premiums as the dependent variable
EU-prices	0.00001578	0.00000860	−0.00000338 – 0.00003494	1.83493479	0.09639450	0.606	0.528
Target population	−0.00003976	0.00001360	−0.00007005 – − 0.00000946	−2.92431420	0.01518788*
Constant	11.02820319	0.13649721	10.72406846–11.33233792	80.79435053	0.00000000*
(6) Bivariate Regression model using log EU-prices and target population, and log additive premiums as dependent variable
Log EU-prices	0.14680259	0.06653394	−0.00144427 – 0.29504945	2.20643159	0.05187319	0.646	0.575
Target population	−0.00003672	0.00001317	−0.00006606 – --0.00000738	−2.788982	0.0191532*
Constant	9.90990728	0.57996394	8.61766708–11.20214748	17.08710928	0.00000001
(7) Multivariate regression model using statistical significant variables, study design, and log additive premiums as the dependent variable
EU-prices	0.00000695	0.00000928	−0.00001405 – 0.00002794	0.74851855	0.47325401	0.707	0.610
Target population	−0.00004912	0.00001344	−0.00007953 – − 0.00001870	−3.6531866	0.00529125*
Study design trichotomized	0.18888016	0.10707861	−0.05334849 – 0.43110881	1.76393916	0.11156758
Constant	10.71083426	0.21852857	10.21648828–11.20518023	49.01342718	0.00000000*
*(8) Basis regression model with interaction AnTCtarget population, trichotomized study design, and log additive premiums as the dependent variable**
EU Prices	0.00001430	0.00001280	−0.00001859 – 0.00004719	1.11734172	0.31464184	0.878	0.708
Comparable drugs	−0.00000489	0.00000346	−0.00001379 – 0.00000400	−1.41398786	0.21649968
Added benefit	−0.26610636	0.21675823	−0.82330113 – 0.29108840	−1.22766442	0.27421249
AnTC ACT	−0.00000604	0.00000394	−0.00001616 – 0.00000409	−1.53330417	0.18577935
Target population	−0.00019253	0.00005941	−0.00034526 – − 0.00003980	−3.24045751	0.02293760*
AnTC ACT*Tar. pop	0.0000000029	0.00000000	0.00000000–0.00000001	2.50391081	0.05423011*
Study design trichotomized	0.29015387	0.13996625	−0.06964081 – 0.64994856	2.07302748	0.09288142
Constant	11.81575737	0.51914558	10.48125116–13.15026357	22.76000749	0.00000304*
Multiplicative premiums
(9) Basis regression model using all variables untransformed, and multiplicative premiums as the dependent variable
EU Prices	0.01863379	0.03046329	−0.0559072 – 0.09317478	0.61167992	0.56319335	0.708	0.417
Comparable drugs	−0.0170363	0.00722779	−0.0347221 – 0.00064944	−2.3570588	0.05651068
Added benefit	318.494844	325.143866	−477.10353 – 1114.09322	0.97955052	0.36513746
AnTC ACT	0.00768265	0.00851777	−0.0131596 – 0.02852487	0.90195532	0.40183525
Study design dichotomized	−606.94617	480.68369	− 1783.1368 – 569.244448	−1.2626727	0.25356019
Target population	−0.0694163	0.03667623	−0.1591598 – 0.02032722	−1.8926775	0.10725321
Constant	1329.140422	612.8264012	−170.39176 – 2828.67261	2.168869389	0.073175976
(10) Basis regression model using all variables untransformed, and log multiplicative premiums as the dependent variable
EU Prices	0.00004607	0.00009979	0.12277548–9.94718239	0.46161051	0.66062263	0.815	0.630
Comparable drugs	−0.00005089	0.00002368	−0.00019812 – 0.00029025	−2.14954836	0.07515311
Added benefit	2.23125516	1.06511407	−0.00010883 – 0.00000704	2.09485090	0.08105271
AnTC ACT	−0.00000966	0.00002790	−0.37498507 – 4.83749539	−0.34604099	0.74112304
Study design dichotomized	−2.19341764	1.57463515	−0.00007793 – 0.00005862	−1.39296880	0.21305128
Target population	−0.00025771	0.00012014	−6.04641104 – 1.65957577	−2.14498038	0.07562852
Constant	5.03497894	2.00751141	−0.00055169 – 0.00003628	2.50806990	0.04602317*
(11) Basis regression model using all variables untransformed, trichotomized study design, and log multiplicative premiums as the dependent variable
EU Prices	0.00002793	0.00010268	−0.00022332 – 0.00027919	0.27202759	0.79471928	0.822	0.646
Comparable drugs	−0.00004310	0.00002491	−0.00010406 – 0.00001786	−1.72989859	0.13437373
Added benefit	0.81020226	1.23677559	−2.21607858 – 3.83648311	0.65509238	0.53669959
AnTC ACT	−0.00001518	0.00002732	−0.00008202 – 0.00005167	− 0.55547716	0.59865283
Study design trichotomized	1.51393827	1.00119466	−0.93589681 – 3.96377335	1.51213179	0.18125773
Target population	−0.00021019	0.00010064	−0.00045646 – 0.00003607	−2.08848182	0.08176979
Constant	2.41624100	2.26119548	−3.11670503 – 7.94918702	1.06856794	0.32635841
(12) Univariate regression model using log AnTC ACT, and log multiplicative premiums as the dependent variable
Log AnTC ACT	−0.931522444	0.036401089	−1.0116407 – − 0.8514042	−25.59051002	0.000000000037*	0.983	0.981
Constant	10.68460638	0.326107398	9.96684884–11.4023639	32.76407232	0.000000000003*	0.983	0.981
(13) Univariate regression model using log AnTC ACT, trichotomized study design, and log multiplicative premiums as the dependent variable
Log AnTC ACT	−0.9010848	0.04282724	−0.9965099 – − 0.8056598	−21.03999339	0.0000000013*	0.985	0.983
Study design trichotomized	0.2069238	0.16343973	−0.1572426 – 0.57109022	1.266055713	0.234191404
Constant	9.947609983	0.663086674	8.4701608–11.4250592	15.00197541	0.0000000349*

adj adjusted, AnTC ACT Annual therapeutic costs of appropriate comparative therapy, CI confidence interval, SE standard error
* ≤ 0.05

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ISSN: 2191-1991

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