Randomized Clinical Trials: the Holy...

Randomized Clinical Trials: the Holy Grail

PRIMARY EFFICACY SUBGROUP RESULTS (mITT)

ASA

ASA + thienopyridine 0.86 (0.75 -0.98) 0.34 0.69 (0.45 -1.05)

STEMI NSTEMI UA

0.85 (0.70 - 1.03)

0.85 (0.68 - 1.06)

0.82 (0.62 - 1.07)

0.96

<65 Years

65 Years

0.83 (0.70 - 0.99)

0.84 (0.70 - 1.01)

0.94

Male

Female

0.87 (0.75 - 1.01)

0.77 (0.60 - 0.99)

0.40

Weight <60 kg

Weight 60 to <90 kg

Weight 90 kg

0.83 (0.56 - 1.25)

0.85 (0.72 - 0.99)

0.83 (0.64 - 1.08)

0.98

Prior MI

No Prior MI

0.83 (0.68 - 1.01)

0.85 (0.72 - 1.01)

0.80

0.5 0.8 1.25 2.0 1.0

Diabetes Mellitus

No Diabetes Mellitus

0.96 (0.77 - 1.20)

0.78 (0.67 - 0.92)

0.14

Creatinine Cl <50 mL /min

Creatinine Cl > 50 mL /min

0.88 (0.62 - 1.26)

0.84 (0.73 - 0.96)

0.82

0.57 (0.33 - 0.97) North America

South America Western Europe Eastern Europe

Asia Other

0.89 (0.59 - 1.34)

0.90 (0.59 - 1.37)

0.83 (0.69 - 1.00)

0.86 (0.63 - 1.17)

0.92 (0.60 - 1.39)

0.80

Overall 0.84 (0.74 0.96)

HR (95% CI) P interaction

Rivaroxaban Better Placebo Better

RCTs and subgroup analysis

Study CURE (3) CURRENT OASIS 7(1) TRITON TIMI (3)* PLATO (7) CAPRIE(3) CHARISMA(3) RE-LY (6) ROCKET AF(1) ARISTOTLE

…What it has been said about subgroup analysis

The answer to a RCT that does not confirm one’s beliefs is not the conduct of several subanalyses until one can see what one believes. Rather the answer is to re-examine one’s beliefs carefully. Subgroup analyses are particularly prone to over interpretation, and one is tempted to suggest ”don’t do it (or at least don’t believe it) for many trials, but this suggestion is probably contrary to human nature. Subgroup analysis is a machine for generating false negatives

“. . . some investigators selectively report

only the more interesting subgroup

analyses, thereby leaving the reader (and

us) unaware of how many less exciting

subgroup analyses were looked at and not

mentioned”. Disappointingly, most trials

reporting subgroup analyses noted a

subgroup difference that was highlighted in

the conclusions—so much for cautious

interpretation! Lancet 2000;355:1064

Subgroup analysis

Do we need them?

Usually small groups or excluded as Elderly, Women , PVD, Stroke CABG, CKD, Bleeding

When to believe a subgroup analysis

Large RCT How many subgroup analyses were performed?

◦ The larger the number, the larger the possibility of a spurious finding.

Is the Magnitude of the Subgroup Difference

Large? The larger the difference between the observed effects in particular subgroups,

the more plausible that the difference is real.

Is the Subgroup Difference Consistent Across

Studies? ◦ Consult meta-analyses and systematic reviews

Is it a post hoc or an ad hoc analysis?

◦ The credibility of any apparent subgroup difference that arises out

of post hoc rather than a priori hypotheses is questionable.

◦ Hypothesis-generating vs. hypothesis testing

Subgroup analysis after a borderline or negative RCTrial

CAPRIE: primary efficacy end-point.

Subgroup-analysis

-60 -50 -40 -30 -20 -10 0 10 20 30 40 50 60 Aspirin better Clopidogrel better

Relative Risk Reduction (%)

Stroke (p/ys=12033)

AMI (p/ys 11630)

PAD (p/ys 11592)

All patients (p/ys=35155)

p=0,26

p=0,66

p=0,0028

p=0,043

CAPRIE Lancet 1996;348:1329–1339.

Population RR (95% CI) p value

Documented AT 0.88 (0.77, 0.998)

0.046

(n=12153)

Risk Factors Only 1.20 (0.91, 1.59) 0.20 (n=3284)

Overall Population* 0.93 (0.83, 1.05) 0.22 (n=15603)

Primary Efficacy Results (MI/Stroke/CV Death) by Pre-Specified Entry Category

* A statistical test for interaction showed marginally significant heterogeneity (p=0.045) in treatment response for the pre-specified subgroups of symptomatic and asymptomatic patients AT=Atherothrombosis

0.6 0.8 1.4 1.2 Clopidogrel + ASA Better

Placebo + ASA Better

1.6 0.4

Adapted from Bhatt DL, Fox KA, Hacke W, et al. NEJM 2006 – In press

Most subgroup findings tend to exaggerate reality. Be especially suspicious of investigators highlighting a subgroup treatment effect in a trial with no overall treatment effect. They are usually superfluous subgroup salvages of otherwise indeterminate (negative) trials

Subgroup analysis after a positive trial

DM

n:3146

n:4662

n: 7647

Diabetes Mellitus

Ticagrelor (solid lines) and

clopidogrel (dotted lines) groups in

patients with levels of HbA1c at

baseline above median of 6% (blue

lines) and below median of 6% (red

lines).

JJames S et al. Eur Heart J 2010;eurheartj.ehq325

major bleeding

CV death, MI, and stroke

Not all trials provide perfect consistency

Robert Doisneau, Paris 1948

Subgroup analyses are an important part of the analysis of a RCT. However, they are commonly overinterpreted and can lead to further research that is misguided or, worse, to suboptimal patient care. Consider a RCT designed to determine whether a new treatment is more effective than an established treatment and assessed with a test, based on all randomized patients, of the null hypothesis that the treatments have equal efficacy, as measured in terms of the primary end point. Then, subgroup analyses are conducted to assess whether different types of patients respond differently to the new treatment. This sounds simple enough, but there are several important sources of confusion and uncertainty regarding such subgroup analyses

Ευρήματα από ανάλυση υπο-ομάδων

• Βασική αρχή: Εάν υπάρχει μια (μέτρια) διαφορά

ανάμεσα σε δύο θεραπείες όσον αφορά κάποιο σύμβαμα,

τότε η διαφορά αυτή μπορεί να είναι μεγαλύτερη ή

μικρότερη σε διακριτές υπo-ομάδες ασθενών αλλά είναι

απίθανο να είναι αντίθετη

Προτεινόμενες συστάσεις

σχετικά με την ανάλυση υπο-ομάδων

• Περιορισμός αναλύσεων σε ΠΡΟ-καθορισμένες υπο-

ομάδες με γνώμονα κάποια λογική παθοφυσιολογική βάση

προηγούμενης έρευνας

• Ανάλυση μόνο εφόσον υπάρχει στατιστική σημαντικότητα

στο συνολικό αποτέλεσμα

• Διόρθωση τιμής p για πολλαπλές συγκρίσεις (0.05/n, πχ

εάν γίνουν 20 συγκρίσεις να απαιτείται p<0.05/20=0.0025)

• Να θεωρείται ότι τα ευρήματα απαιτούν περαιτέρω έρευνα

και ότι δεν είναι αποδεικτικά

• Να μην δίνεται υπερβολική σημασία

Medical research and patients are best served when subgroup analyses are well planed and appropriately analyzed and when conclusion and recommendations about clinical practice are guided by the strength of the evidence.

TRITON: Numerical reduction in CV death and significant

reduction in MI [5% (40% relative)] with prasugrel in DM pts

Relatively lower reduction in MI with ticagrelor in PLATO may

be explained by

◦ Higher average loading dose of clopidogrel in the clopidogrel arm

◦ Pre-treatment with clopidogrel in 50% pts in the ticagrelor arm

◦ TRITON results depend on early periprocedural MI, detection facilitated by

delay of subject enrolment until after CANG. PLATO enrolled pts soon after

the index event, making early MI detection more difficult. Thus, any

apparent difference in MI results between trials likely results from study

design rather than actual outcome.

PLATO diabetes…

High platelet reactivity in DM

◦ Higher dose of ticagrelor could have resulted in greater clinical benefit???

Predicted steady-state plasma exposure of ticagrelor and its active metabolite not

different in patients with or without DM (AZ internal data)

Very high levels of platelet inhibition may not be sufficient

for adequate protection against ischaemic events in

patients with DM.

◦ The prothrombotic condition that DM constitutes may require anti-thrombin or

other long-term anti-coagulation therapy for a more general prevention of CV

events...

PLATO diabetes…

ROCKET- AF trial- Rivaroxaban in AF Pts with Moderate Renal Impairment

• 14264 ασθενείς με ΚΜ με CHADS2 score ≥ 2 και μέτρια νεφρική δυσλειτουργία: rivaroxaban 20 mg/day or 15 mg/day if CrCl 30–49 mL/min or dose-adjusted warfarin (INR: 2.0– 3.0)

- Μεγαλύτερη συχνότητα μειζόνων και κλινικά σημαντικών αιμορραγιών σε ασθενείς με ΝΑ, ανεξάρτητα από το είδος της θεραπείας

- Παρόμοια συχνότητα αιμορραγιών με μειωμένη δοσολογία rivaroxaban και θεραπείας με warfarin

- Λιγότερες θανατηφόρες αιμορραγίες με rivaroxaban (0.28 vs. 0.74% per 100 p-y; P = 0.047)

Fox K, et al: Eur Heart J 2011; 32: 2387– 2394

Yusuf S, et al. NEJM 2001; 345: 494‐502

Overall

Diabetes

No Diabetes

12562 11.4 9.3

2840 9722 9.9 7.9

14.2 16.7

Aspirin effect on stroke in women

The Canadian Cooperative Study Group. NEJM 1978;299:53-59.

Antiplatelet Trialists’ Collaboration. BMJ. 1994;308:81-106.

Is There External Evidence That Supports the Hypothesized Subgroup Difference? ◦ Does the subgroup effect make sense?

Different populations (including animal studies)

Similar interventions (drug-class effect)

Similar outcomes (surrogate outcomes)

15.9%

22.3%

0%

5%

10%

15%

20%

25%

Ann

ual e

vent

rat

e %

Clopidogrel’s benefit over ASA is amplified in patients with a previous CABG

Bhatt et al. J Am Coll Cardiol 2000;35(Suppl A):383 Bhatt, unpublished data

Overall benefit: p = 0.001; multivariate analysis

Stroke, MI, VD, hospitalization for ischemic events/bleeding Events prevented / 1000 patients per year over ASA

Clopidogrel

ASA

6

Symptomatic Cohort: Primary Outcome (MI/Stroke/CV Death)† by Entry Criteria*

†MI (fatal or non-fatal), stroke (fatal or non-fatal), or cardiovascular death *Patients may have met more than one inclusion criteria All patients received ASA 75-162 mg/day

Cerebrovascular (n=4320)

Placebo +ASA (9.6%)

RRR: 16.0% p=0.088

Clopidogrel + ASA (8.1%)

0

2

4

6

8

10

12

Months since randomization 0 6 12 18 24 30

Coronary (n=5835)

Clopidogrel + ASA (6.5%)

Placebo + ASA (7.4%)

Prim

ary o

utc

om

e e

ven

t rate

(%

)

Months since randomization

RRR: 13.9% p=0.130

0

2

4

6

8

10

12

0 6 12 18 24 30

PAD (n=2838)

Placebo + ASA (8.7%)

Clopidogrel + ASA (7.6%)

RRR: 13.1% p=0.285

0

2

4

6

8

10

12

Months since randomization

0 6 12 18 24 30

Bhatt DL. Presented ateeting - March 2006

CABG and P2Y12 Inhibitors seccation

Common group for subanalysis

Elderly - Women Diabetes mellitus Stroke (history or not)

PVD CABG CKD (patients with CKD were excluded from75%

of published CAD trials) Kidney Intern 2006