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. 2016 Apr 27;7:1541–1550. doi: 10.1016/j.dib.2016.04.059

All cholesterol-lowering interventions are expected to reduce stroke: Confirmatory data from IMPROVE-IT

Raffaele De Caterina a,⁎, Tanya Salvatore a, Roberto Marchioli b
PMCID: PMC4865673  PMID: 27222850

Abstract

The relationship of cholesterol with stroke is much less clear than its relationship with myocardial infarction, thus confounding the interpretation of results with cholesterol-lowering trials (Di Napoli et al., 2002) [1], (De Caterina et al., 2010) [2]). IMPROVE-IT data ((Cannon et al. 2015) [3]), showing a 13.3% reduction in total cholesterol at one year in association with a hazard ratio (HR) of 0.i86 for total stroke during the trial, are very closely aligned with the relative risk of 0.90 predicted based on the totality of lipid lowering interventions ((De Caterina et al., 2016) [4]). We here provide the data from the original trials used to construct this meta-analysis, with the now added additional data from IMPROVE-IT, well-fitting the previously found meta-regression line.

These data are important to predict stroke outcomes in currently ongoing trials now testing PCSK9 or cholesterol ester transfer protein inhibitors.

Keywords: Epidemiology, Cholesterol, Cholesterol lowering, Statins, Stroke, Risk prediction, Ezetimibe

Specifications Table

Subject area Biology/Medicine
More specific subject area Lipid-lowering intervention trials in cardiovascular disease prevention
Type of data Table
How data was acquired Literature data extraction
Data format Raw
Experimental factors No data pretreatment-calculation of percent reduction in stroke as a function of percent reduction in total cholesterol in each of the original source trials
Experimental features Meta-regression now fitting the recently published IMPROVE-IT data into the meta-regression
Data source location n/a
Data accessibility Data are within this article
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Value of the data

  • •

    These data, as obtained through already published literature reinforce the idea that also reduction of stroke, contrary to what previously believed, can be explained by reduction in cholesterol (total cholesterol in this analysis), both in statin and non-statin trials.

  • •

    Recently published data from IMPROVE-IT perfectly fit the regression line from other source data on such relationship.

  • •

    These results now allow a prediction of the reduction in stroke in trials now testing the PCSK9 inhibitors and the cholesterol ester transfer protein (CETP) inhibitor anacetrapib.

1. Data

Data provided here are the characteristics of source trials used for the construction of the meta-regression of reduction in stroke as a function of reduction in total cholesterol.

2. Experimental design, materials and methods

We had previously carried out a meta-regression by using inverse variance weighted linear regression of the log RR for total stroke against the percent of TC reduction as the explanatory variable. Weights in each study were the reciprocals of the variances for the logarithm RR for stroke. The meta-regression had yielded the following equation:

ln(totalstrokeRR)=0.00518−0.00793(%TCreduction)

The regression coefficient for percent TC reduction was significantly different from zero (p=0.0017). This equation indicates that some benefit from cholesterol-lowering intervention on the risk of stroke can be expected when the percent reduction of serum cholesterol is >2–3%, the clinical benefit becoming statically significant when TC is reduced by ~8%.

We have now compared the reduction in stroke observed in IMPROVE-IT [3] with that calculated from our previous meta-analysis of all lipid lowering interventions reporting effects on stroke, in all trials as previously reported and as shown in Table 1. IMPROVE-IT [3] has now shown that a 13.3% reduction in total cholesterol at one year was associated with a hazard ratio (HR) of 0.86 for total stroke during the trial. This result is very closely aligned with the relative risk of 0.90 predicted on the basis of the totality of lipid lowering interventions [2], [5].

Table 1.

Description of the trials selected – demographic characteristics.

TRIAL, [ref No], Year of publication Designa Follow-upb Total patients Total stroke Fatal stroke Non-fatal stroke AGE (mean) SMK (%) DM (%) HBP (%) PMI (%) PST (%)
Oslo [6], [7], [8],1966 D,op,SE 5 412 3 2 NA 56.0 64.6 10.0 – 100 –
MRC [9], [10],1968 D,op,SE 4 393 2 2 0 – 82.5 0.0 13.0 100 –
LA [11],1969 D,b,PS 8 846 38 12 26 65.5 66.4 – – 20.1 12.5
Newcastle [12],1971 F,b,SE 3.6 497 1 1 0 52.5 65.0 0.0 0.0 23.0 –
Scottish [13], [14],1971 F,b,SE 3.4 717 5 5 0 52.1 56.6 0.0 – 72.9 –
VA [15],1974 F,b,SE 4.5 532 60 13 NA – – 23.5 64.5 – 16.0
CDP [16], [17], [18], [19],1975 F O,b,SE 6.2 5011 161 34 NA 52.0 37.9 5.0 20.0 100.0 2.0
Dorr [20],1978 O,b,PS 1.9 1094 1 1 0 50.5 – 13.7 16.2 6.2 0.5
WHO [21], [22], [23], [24],1980 F,b,PR 5.3 10627 NA 25 31 45.9 56.0 0.0 0.0 0.0 0.0
McCaughan [25],1981 O,b,PS 1 118 0 0 NA 49.8 44.6 – – 33.9 –
LRC-CPPT [26],1984 O,b,PR 7.4 3806 35 4 NA 47.7 37.5 0.0 0.0 0.0 0.0
CLAS I [27], [28],1987 O,b,SE 2 188 0 0 0 54.2 0.0 0.0 0.0 – –
Helsinki [29], [30],1987 F,b,PR 5 4081 10 10 0 47.3 36.2 2.6 14.0 0.0 –
Stockholm [31], [32],1988 O,op,SE 5 555 11 6 5 59.8 67.3 3.3 36.0 100.0 –
Minnesota [33],1989 D,b,PR 1.1 9057 43 43 NA 48.0 – – – – –
FATS [34],1990 S O,b,SE 2.7 98 0 0 NA 47.3 23.9 0.0 34.7 43.6 –
POSCH [35], [36], [37], [38],1990 B,op,SE 9.7 838 29 3 NA 51.0 35.0 0.1 0.0 100.0 0.0
EXCEL [39], [40], [41],1991 S,b,PS 0.9 8245 11 1 NA 55.8 18.3 1.1 39.6 – 3.9
Singh [42], [43],1992 D,b,SE 1 406 3 3 0 51.3 35.4 18.0 22.0 100.0 –
Frick [44],1993 F,b,SE 5 628 2 2 0 48.6 38.8 – – 9.0 –
MARS [45], [46],1993 S,b,SE 2.2 270 3 0 NA 58.0 – 0.0 46.0 60.0 –
PMSG-CRP [47],1993 S,b,SE 0.5 1062 3 0 3 55.0 28.7 0.0 47.5 34.5 –
4 S [48], [49], [50],1994 S,b,SE 5.5 4444 132 26 NA 58.6 25.6 4.5 26.0 79.3 0.0
ACAPS [51],1994 S,b,PR 2.8 919 5 2 3 61.7 11.9 2.3 28.8 0.0 0.0
CCAIT [52],1994 S,b,SE 2 331 1 0 NA 53.0 27.0 14.0 37.0 54.0 18.0
LR [53],1994 S,b,SE 0.5 404 1 0 1 62.0 49.8 11.6 48.8 25.0 –
Lyon [54],1994 D,b,SE 2.3 605 3 0 3 53.5 6.2 – 0.0 100.0 –
MAAS [53],1994 S,b,SE 4 381 3 0 NA 55.3 23.9 0.0 – 54.3 –
PLAC-I [55], [56], [57], [58],1994 S,b,SE 2.3 408 2 0 2 57.0 16.5 0.0 45.5 43.5 0.0
PLAC-II [57], [59], [60],1994 S,b,SE 3 151 4 1 NA 62.5 12.1 – 0.0 63.8 –
Regress [61], [62],1994 S,b,SE 2 884 2 0 2 56.2 27.7 0.1 27.8 47.4 –
KAPS [63],1995 S,b,PS 3 447 6 1 5 57.4 26.2 2.5 33.1 7.6 –
CARE [64], [65],1996 S,b,SE 5 4159 128 16 NA 59.0 21.0 14.5 42.5 100 –
WOSCOPS [66],1996 S,b,PR 4.9 6595 97 10 NA 55.2 44.0 1.0 15.5 0.0 0.0
CIS [67],1997 S,b,SE 2.3 254 0 0 0 49.3 84.3 0.0 – – –
LOCAT [68],1997 F,b,SE 2.5 395 0 0 0 59.2 – 0.0 40.0 55.2 –
PCABGT [69],1997 S,op,SE 4.3 1351 34 NA NA 61.5 11.3 8.6 – 49.3 –
PREDICT [70],1997 S,b,SE 0.5 695 1 1 0 58.3 33.7 7.2 30.7 37.1 1.9
AFCAPS [71],1998 S,b,PR 5.2 6605 31 NA NA 58.0 12.4 2.4 21.9 0.0 0.0
LIPID [72], [73], [74],1998 S,b,SE 6.1 9014 373 49 NA 61.5 9.6 8.7 41.7 63.8 4.1
Mas [75],1999 O,b,SE 0.5 437 1 NA NA 58.0 32.7 17.8 82.2 – 3.9
GISSI P [76],2000 S,op,SE 1.9 4271 39 8 31 60.0 11.9 13.6 36.5 100.0 –
SCAT [77],2000 S,b,SE 4.0 460 11 9 NA 61.0 15.0 10.9 35.2 70.4 –
VA-HIT [78],2000 F,b,SE 5.1 2531 134 12 NA 64.0 20.5 24.5 57.0 61.0 –
BCAPS [79],2001 S,b,SE 3 793 8 NA NA 61.8 30.8 3.0 12.1 – –
BIP [80],2001 F,b,SE 6.2 3090 149 NA NA 60.1 11.8 10.0 32.4 77.9 1.1
DAIS [81], [82], [83],2001 F,b,SE 3.3 418 12 NA NA 56.8 14.8 100.0 51.4 – –
HATS [84],2001 S,b,SE 3 160 4 0 4 53.0 24.0 16.0 49.0 55 –
ALLHAT-LLT [85],2002 S,op,PR 4.8 10355 440 109 NA 66.4 23.2 35.1 100.0 0.0 –
FAST [86],2002 S O,PR 2 246 0 0 0 66.1 59.3 22.8 41.5 – –
GREACE [87],2002 S,op,SE 3 1600 26 1 NA 58.5 – 19.6 42.9 81.2 –
HPS [88], [89],2002 S,b,SE 5 20536 1029 215 865 64.0 14.1 29.0 41.0 41.0 –
LEADER [90], [91],2002 F,b,SE 4.6 1568 109 22 97 68.2 37.8 17.1 – 19.8 11.7
LIEM [92],2002 S,b,SE 1 540 3 3 0 60.5 – – – 100.0 –
LIPS [93],2002 S,b,SE 3.9 1677 3 3 NA 60.0 26.6 12.1 38.6 44.4 2.6
PROSPER [94],2002 S,b,PS 2.2 5804 266 36 235 75.4 26.8 10.7 61.9 13.4 –
ALERT [95], [96],2003 S,b,PS 5.1 2102 104 31 NA 50.0 18.5 18.8 74.9 3.1 5.8
ASCOT-LLA [97],2003 S,b,PR 3.2 10305 210 NA NA 63.0 32.7 24.6 100.0 0.0 –
Mohler [98],2003 S,b,SE 1 354 2 1 1 68.0 40.4 17.5 – – –
ALLIANCE [99],2004 S,b,SE 4.3 2442 74 NA NA 61.2 19.5 22.1 – 57.8 6.6
ARBITER2 [100],2004 O,b,SE 1 167 1 NA NA 67.5 10.2 27.5 74.9 49.7 –
BaeJH [101],2004 S,b,SE 6 205 2 0 2 60.0 41.5 29.8 48.3 12.2 –
CARDS [102],2004 S,b,PR 3.9 2838 60 6 50 62.0 22.2 100.0 83.8 0.0 0.0
PCS [103],2004 S,b,SE 5 120 7 NA NA 59.6 67.5 17.5 59.2 – –
4D [104], [105],2005 S,b,SE 4 1255 103 40 65 65.7 8.6 100.0 – 17.6 –
FIELD [106], [107],2005 F,b,SE 5 9795 333 NA NA 62.2 9.4 100.0 56.6 5.0 3.5
Makuuchi [108],2005 S,op,SE 4.5 303 6 1 NA 58.9 41.9 33.3 51.5 62.0 –
Stone [109],2005 S,b,SE 1 300 2 NA NA – 0.0 16.0 63.6 39.3 –
ASPEN prim [110],2006 S,b,PR 4 1905 56 NA NA 60.5 13.2 100.0 52.3 0.0 –
ASPEN sec [110],2006 S,b,SE 4 505 16 NA NA 63.2 9.7 100.0 65.5 78.2 –
SPARCL [111],2006 S,b,SE 4.9 4731 576 65 527 62.7 19.2 16.7 61.9 30.9 69.1
WHI-DM [112],2006 D,o,PS 8.1 48835 1076 150 935 62.3 6.7 – 42.9 1.9 1.1
CORONA ,[120],2007 S,b,SE 2.7 5011 NA 67 197 73.0 8.6 29.5 63.4 59.9 12.4
ARISE [113],2008 O,b,SE 2 6144 54 0 64 65.0 13.5 37.0 72.0 72.0 –
CCSPS [114],2008 O,b,SE 4.5 4870 NA 25 NA 58.9 34.5 12.5 55.5 100.0 –
GISSI-HF [115],2008 S,b,SE 3.9 4574 148 67 86 68.0 14.1 26.1 54.3 – 4.5
JUPITER [116], [117],2008 S,b,PR 1.9 17802 97 NA 88 66.0 15.8 0.0 57.3 0.0 0.0
OACIS lipid [118],2008 S,o,SE 0.7 353 2 NA NA 63.2 57.4 31.7 747.6 100.0 7.3
IMPROVE-IT[119],2015 O,b,SE 6 18.144 641 NA NA 64.0 33.0 27.2 61.5 21.0 NA
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AGE mean age; SMK smoking status; DM diabetes mellitus; HBP high blood pressure; PMI previous myocardial infarction; PST previous stroke.

a

DESIGN: the first letter indicates the type of lipid lowering intervention (D: diet, S; statins, F: fibrates, O: other drugs, B: ileal bypass or other surgery); the second letter indicates the study design (op: open; b blind); the last letter indicates the clinical setting (PR: primary, SE: secondary, PS: primary and secondary)

b

FOLLOW-UP indicates mean duration (year), in its absence the maximum follow-up duration is indicated (in italics);

3. Original Source data

.

Footnotes

Appendix A

Supplementary data associated with this article can be found in the online version at doi:10.1016/j.dib.2016.04.059.

Appendix A. Supplementary material

Supplementary material

mmc1.doc (55KB, doc)

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