The Use of External Controls in FDA Regulatory Decision Making

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Abstract

The regulatory standards of the United States Food and Drug Administration (FDA) require substantial evidence of effectiveness from adequate and well-controlled trials that typically use a valid comparison to an internal concurrent control. However, when it is not feasible or ethical to use an internal control, particularly in rare disease populations, relying on external controls may be acceptable. To better understand the use of external controls to support product development and approval, we reviewed FDA regulatory approval decisions between 2000 and 2019 for drug and biologic products to identify pivotal studies that leveraged external controls, with a focus on select therapeutic areas. Forty-five approvals were identified where FDA accepted external control data in their benefit/risk assessment; they did so for many reasons including the rare nature of the disease, ethical concerns regarding use of a placebo or no-treatment arm, the seriousness of the condition, and the high unmet medical need. Retrospective natural history data, including retrospective reviews of patient records, was the most common source of external control (44%). Other types of external control were baseline control (33%); published data (11%); and data from a previous clinical study (11%). To gain further insights, a comprehensive evaluation of selected approvals utilizing different types of external control is provided to highlight the variety of approaches used by sponsors and the challenges encountered in supporting product development and FDA decision making; particularly, the value and use of retrospective natural history in the development of products for rare diseases. Education on the use of external controls based on FDA regulatory precedent will allow for continued use and broader application of innovative approaches to clinical trial design, while avoiding delays in product development for rare diseases. Learnings from this review also highlight the need to update regulatory guidance to acknowledge the utility of external controls, particularly retrospective natural history data.

Keywords: External controls, Retrospective natural history, Rare disease, Baseline controls, Historical controls

Introduction

The United States Food and Drug Administration’s (FDA’s) drug approval standard requires substantial evidence 1 of effectiveness from adequate and well-controlled investigations 2 including clinical investigations that incorporate, among other factors, a valid comparison to a control, to “distinguish the effect of a drug from other influences [1], such as spontaneous change in the course of the disease, placebo effect, or a biased observation” [1]. The FDA, consistent with regulations (21 CFR 314.126) and ICH E10 guidance, generally recognizes internally 3 controlled [1] study designs (placebo, active treatment, dose comparison, no-treatment) where “the control group and test groups are chosen from the same population and treated concurrently” [1]. However, FDA does recognize that in studies for diseases with high and predictable mortality or progressive morbidity, and in particular for certain rare diseases, when it is not feasible or would not be considered ethical to use an “internal control”, reliance on “external controls” 4 , 5 may be acceptable [1, 2]. When a trial is externally controlled, the results of treatment with the test drug may be compared with experience derived from the adequately documented natural history of the disease or condition, a registry, published literature, or patient medical records [3, 4]. Patients may also serve as their own controls [1] (by comparison to their status before therapy). 6

In this article, we briefly review guidance documents discussing the use of external controls and provide examples of approvals where external controls were deemed satisfactory to meet FDA standards for approval. We highlight some methodological and statistical considerations and advocate for a change in guidance to promote the continued use of external controls, including retrospective natural history, in drug development and approval.

Definitions and Categories of External Controls

The ICH E10 guidance defines an externally controlled trial as “one in which the control group consists of patients who are not of part of the randomized study as the group receiving the investigational agent i.e., there is no concurrently randomized control group” [1].

External controls can be categorized by the time the subject data were collected into [1, 3, 4]:

Concurrent External Controls: The control group is based on subject level data collected at the same time as the treatment arm but in another setting [1]. An example is data from a concurrent prospective natural history 7 study as the control arm for an open-label treatment study.

Retrospectively Collected Natural History: Subject level data collected retrospectively from a natural history study. Such data may be extracted from sources such as existing medical records (for example patient charts [3, 4]), or from a previously conducted registry. 8

Published Data: Data only available in the published literature. Such published data may have been derived from individual cases, however, it is distinguished from retrospectively collected natural history data based on the lack of access to subject level data and the lack of detailed information on data collection methodology.

Previous Clinical Study: Subject level data from an arm of a previously completed clinical study [3] in the same indication and/or patient population.

Baseline-Controlled Study: Historical control derived from a patient’s baseline (“patient baseline control or baseline-controlled study”) [1]. The data could be collected over a period of time prior to initiation of treatment, and patients’ status on therapy is compared with status before therapy.

Of note, the term “real-world-evidence” (RWE) 9 has recently been used to describe data sourced from natural history studies, chart reviews, registries and other settings and used as a comparison arm for a single-arm study [5–7].

Summary of Current Guidance Discussing Use of External Controls

Several guidance documents discuss the use of external controls as a comparator in clinical trials [1–4, 8–14] (see Table ​ Table1), 1 ), particularly for rare diseases. The ICH E10 guideline on “Choice of control group and related issues in clinical trials ” [1] provides a comprehensive discussion on such controls, stating “The choice of the control group should be considered in the context of available standard therapies, the adequacy of the evidence to support the chosen design, and ethical considerations.” While the guideline emphasizes that in most situations, an internal concurrent control is necessary to minimize bias and obtain robust statistical analyses, it also highlights that this may not always be feasible. In addition, it is broadly recognized by developers and researchers that initiation of prospective natural history studies for use as a source of external controls may not be feasible, especially in rare diseases, thus alternative approaches, such as the use of retrospective natural history data, have frequently been leveraged to support product development and approval. ICH E10 envisages this flexibility by acknowledging the acceptability of external controls from a group of patients treated at an earlier time (“historical”). Additionally, the FDA guidance “Rare diseases: common issues in drug development” [4] emphasizes that product development should not be delayed due to the lack of prospective natural history data. While FDA highlights the use of prospectively collected natural history data as the preferred approach, the guidance specifically, states that “initiation of prospective natural history studies should not delay interventional testing otherwise ready to commence for a serious disease with unmet medical need” [4]. This point abides by a pragmatic approach to product development and underscores the importance of ensuring development can proceed to expedite patient access to treatment.

Table 1

FDA and ICH regulatory guidance discussing the use of external controls

a Guidance for industry

FDA further articulates the importance of flexibility in trial design in the recently published FDA draft guidance on “Demonstrating substantial evidence of effectiveness for human drug and biological products” [2]. The draft guidance indicates that FDA may rely on study designs that produce less certainty (such as externally controlled studies) in some circumstances such as “life-threatening and severely debilitating diseases with an unmet medical need, 10 for certain rare diseases, or potentially even for a more common disease where the availability of existing treatments makes certain design choices infeasible or unethical” [2]. The guidance also notes that a single trial with compelling results compared to either an external or concurrent control, could further be supported by data from separate sources (e.g., a natural history study, case report forms, or registries) as confirmatory evidence.

Collectively, these guidance documents [1–4, 8–14] reaffirm that use of external controls is acceptable under certain circumstances (see Fig. ​ Fig.1 1 for details) and reinforce the need for flexibility both in guidance as well as in application during product development and FDA decision making.

The use of external control design is most persuasive under the following circumstances

Methods

We searched FDA regulatory approvals between 2000 and 2019 11 for drug and biologic products where pivotal studies employed external controls. We included original marketing applications and supplemental applications for new indications specifically mentioning use of natural history data or historical controls to support a pivotal study. Applications in which natural history data were used in other ways, such as to guide endpoint development or to interpret nonclinical studies, were excluded.

Since the use of external controls appears to be well accepted in the field of oncology [15, 16], we focused our assessment on non-oncology product approvals, concentrating on the FDA divisions responsible for reviewing the following therapeutic areas: gastroenterology and inborn errors of metabolism; neurology; metabolism and endocrinology; reproduction, bone diseases, and urology; and non-malignant hematology. Anti-infectives, vaccines and immunoglobulins were excluded as their development pathways are dictated by guidelines unique to the therapeutic area.

We examined the characteristics of such applications with respect to rare disease status, seriousness of the disease, degree of unmet medical need, and objectivity of the primary endpoint and categorized the source of the external control data.

Results

Based on our search criteria, we identified forty-five products 12 (see Table ​ Table2) 2 ) for which pivotal trials were supported by external controls. Nearly half (49%) of the cases identified were for non-malignant hematological products (Fig. ​ (Fig.2) 2 ) with gastroenterology and inborn errors of metabolism products comprising the second largest category (22%), followed by metabolism and endocrinology products (13%), neurology products (9%), and reproduction, bone diseases and urology products (7%), illustrating that experience with the use of external controls is variable across the Divisions at FDA.

FDA review divisions responsible for the 45 product approvals relying on external controls (2000–2019, select therapeutic areas)

Table 2

Characteristics of US FDA approvals based on external controls 2000–2019 (selected indications; n = 45)—presented in reverse order of approval

Zolgensma

Phase 1, open-label, single-arm, single center, ascending dose (N = 15; 3.4–6.3 months)

Phase 3, open-label, single-arm (N = 21; 3.9 months) c

Esperoct

(recombinant antihemophilic factor) glycoPEGylated-exei

Omegaven

(fish oil triglyceride)

Phase 2–3, open-label (N = 52; < 2 y/o)

Crysvita

Phase 2, open-label, randomized, multicenter, dosing interval dose titration (N = 52; 5–14 y/o); 64 weeks

Phase 2, open-label, randomized, single-arm, multicenter (N = 13; 1–4 y/o); 24 weeks g

Brineura

Tepadina

Exondys 51

Phase 1–2, randomized, multi-dose, placebo-controlled (N = 12; 7–11 y/o); 24 weeks

Open-label extension of the phase 1-2 study (N = 12); 212 weeks

Afstyla

(recombinant single chain analogue of factor VIII)

Phase 1–3, open-label, multicenter, cross-over (N = 146 subjects on prophylactic treatment; ≥ 12 y/o); 8.5 months

Phase 3, open-label, multicenter (N = 84; 0– < 12 y/o); 5.6 months

ProvayBlue

Retrospective chart review of case series (N = 6; 6 days to 69 y/o)

Series of cases from publications (N = 41; 9 days to 80 y/o)

Defitelio

Idelvion

(recombinant fusion von Willebrand Factor)

Kanuma

Vonvendi (recombinant von Willebrand Factor)

Strensiq

infantile- and juvenile-onset hypophosphatasia

Nuwiq

(recombinant antihemophilic factor)

Phase 3, open-label, single-arm, uncontrolled, multicenter (N = 32, adults); ≥ 6 months

Phase 3, open-label, single-arm, uncontrolled, multicenter (N = 56; 2–12 y/o); ≥ 6 months

Cholbam

Open-label, non-randomized study and its extension (N = 44); 21 months

Published case series (N = 15)

Xuriden

Myalept (metreleptin)

Open-label, single-arm, uncontrolled (N = 9; > 14 y/o); 1 year

Open-label, single-arm, uncontrolled (N = 63; 1–14 y/o); 1 year

Vimpat

Tretten

(recombinant coagulation Factor XIII A)

Novoeight

(recombinant antihemophilic factor)

Rixubis

(recombinant Factor IX)

Octaplas

(plasma protein fraction)

None were considered pivotal:

Open-label, non-randomized, parallel group (N = 20)

Phase 2, single-blind, randomized, controlled (N = 55)

Open-label non-randomized (N = 36)

Open-label, randomized (N = 60)

Juxtapid

Signifor

Elelyso

Phase 3, randomized, double-blind, parallel-dose group, multicenter (N = 31; 19–74 y/o - all patients were enzyme replacement therapy naïve); 9 months

Phase 3, open-label, single-arm, multicenter (N = 25 patients switched from imiglucerase to Elelyso; 13–66 y/o); 9 months

Ferriprox

Soliris

Phase 2, open-label, single-arm, multicenter (N = 16; 17–68 y/o); ≥ 26 weeks

Phase 2, open-label, single-arm, multicenter (N = 20; 13–63 y/o); ≥ 26 weeks

Retrospective, open-label, single-arm, multicenter (N = 30; nineteen 2 months to < 18 y/o, and eleven adults); ≥ 26 weeks

Corifact

(Factor XIII concentrate)

Lamictal XR

Anascorp

(centruroides scorpion anti-venom)

Phase 3, randomized, placebo-controlled (N = 8 on drug; 7 on placebo; 1 month to 18.7 y/o)

Supported by four phase 2-3, open-label studies (N = 1,526) using historical data (retrospective chart review; N = 97) as external control

Carbaglu

Hyperammonemia due to N-acetyl

glutamate synthase (NAGS) deficiency

Vpriv

Phase 3, randomized, double-blind, multicenter, parallel-dose group (N = 25; ≥ 4 y/o); 12 months

Phase 3, randomized, double-blind, active-controlled (imiglucerase), parallel group, multicenter (N = 34; 17 received VPRIV; ≥ 3 y/o); 9 months

Phase 3, open-label, single-arm, multicenter (N = 40; patients switched from imiglucerase to VPRIV; ≥ 9 y/o); 12 months

Acthar

Atryn

(recombinant human anti-thrombin)

Phase 3, open-label

Phase 2, open-label

(Pooled patient data N = 31)

Ceprotin

(protein C concentrate)

Implanon

Myozyme

Ammonul

(sodium phenylacetate and sodium benzoate)

Orfadin

Digifab

(ovine digoxin fab injection)

Pharmacokinetic/Pharmacodynamic study in HHVs m (Digifab N = 8 versus Digibind N = 8)

Venofer

(iron sucrose injection)

Phase 2–3, open-label, multicenter, historical-controlled (N = 101); 10 weeks

Open-label, multicenter, baseline-controlled (N = 23)

Open-label, multicenter, baseline-controlled (N = 132)

Cetrotide

Phase 3, randomized, open-label, multicenter, active-controlled o (N = 188 vs 86 on active); 1 to 19 days

Phase 3, non-controlled, open-label, multicenter (N = 346); 1 to 15 days

Phase 3, randomized, open-label, multicenter, active- controlled o (N = 115 versus 39 on active), one dose

Argatroban

Hectorol

Phase 3, open-label, multicenter (N = 28; 23–73 y/o); 20 weeks including 8-week washout period

Phase 3, open-label, multicenter (N = 42; 28–76 y/o); 20 weeks including 8-week washout period

a Rare disease does not necessarily mean the product has orphan drug designation

b Unmet medical need (no existing therapy, inadequate existing therapy, or better safety)

c Study was ongoing

d External control was used for the routine prophylaxis indication only

f Only the pediatric indication relied on use of historical controls

g Study was ongoing and 24-week data were submitted in the BLA and 40-week primary analysis results were submitted during the BLA review process

h Hematopoietic stem-cell transplantation

i Efficacy supplement 013

j When chelation therapy is inadequate

k Efficacy supplement 172

l Efficacy supplement 006

m Healthy human volunteers

n Luteinizing hormone

o Active control was not approved in the US

Overall Trends

The majority (80%; see Table ​ Table3) 3 ) of the approvals relying on external controls were for a rare disease where regulatory flexibility was applied due to the size of the population and/or to the unmet medical need (i.e., no or inadequate available therapy). This is consistent with other reports of FDA flexibility with respect to the quantum of evidence relied upon for the approval of orphan products [15, 17]. Overall, for the therapeutic categories evaluated, approximately one in three (33%) first-time approvals of products for rare diseases relied on external controls over the 20-year period.

Table 3

Characteristics of products approved based upon use of external controls (2000–2019)

a These were products for rare diseases which did not necessarily have an orphan drug designation

Types of External Controls Used to Support Approval

Of the 45 approvals evaluated, historical controls derived retrospectively from natural history data were the most common source (44%) of external control, including retrospective reviews of patient medical records (see Fig. ​ Fig.3). 3 ). While prospectively gathered natural history data sources are preferred based on FDA guidance, none of the external controls included in the regulatory approvals assessed in this review were prospective. Other data sources of external control were less common (baseline control: 33%; published data: 11%; data from a previous clinical study: 11%). A hybrid approach, where external control data were added to a concurrent randomized control arm (placebo and/or active), was used for at least three products (velaglucerase alfa, corticotropin, centruroides anti-venom) developed to treat conditions for which there were no available therapies. Two of these were approved for the treatment of rare pediatric conditions.

Categories of external controls to support product approval by the US FDA (2000–2019, select therapeutic areas)

Objective Versus Subjective Endpoints

The vast majority (87%) of cases identified utilized an objective measure as a primary endpoint. Survival at pre-specified endpoints (sodium phenylacetate and sodium benzoate combination [Ammonul], onasemnogene abeparvovec [Zolgensma]), and urinary free-cortisol concentration (pasireotide diaspartate [Signifor]) are some examples of the objective endpoints used. For the few cases where the endpoint was subjective, the benefit was so large it was unlikely to be due to chance alone. For example, in the case of burosumab (Crysvita, X-linked hypophosphatemia [XLH] in adult and pediatric patients ≥ 1 year, a rare disease), the studies in support of the pediatric indication used data from a retrospective natural history study conducted in 52 children who were on conventional therapies (phosphate/calcitriol) as external controls and a subjective clinician-reported outcome (reduction in total Rickets Severity Scale [RSS] scored by a radiologist) as the endpoint. The large effect size for reduction in RSS (50–59% versus 12% in the historical control 13 ) supported the pediatric approval. Factors that strengthened this case were the assessment of radiographs (from both the retrospective natural history study and children treated with Crysvita) by the same blinded radiologist and the use of three propensity score analyses to mitigate several imbalances in the demographics (i.e., sex and baseline rickets scores) between the treatment and historical control groups. FDA’s statistical review noted that while the comparisons were imperfect they were still supportive of the conclusion that Crysvita is more effective than conventional therapies at correcting rickets in pediatric XLH. Ultimately, FDA determined that the unmet medical need and the totality of data, including improvements in secondary and pharmacodynamic endpoints, supported approval in the pediatric indication.

Examples of Approvals Based on Different Types of External Controls

A relatively recent example of utilizing retrospective natural history data is FDA’s approval of Zolgensma (a gene replacement therapy) for infantile-onset spinal muscular atrophy (SMA) due to biallelic mutations, a rare disease with high unmet need. SMA is a serious, life-threatening disease where untreated patients will either die or require permanent ventilation by 24 months of age. Given the rare nature of the disease, data from 23 patients were successfully used as an external control. In this case, the natural history of SMA was predictable, the efficacy of Zolgensma was objectively measured, there was a large treatment effect (90% alive without ventilation versus 25% based on natural history), and there was evidence of a temporal association with the intervention. 14

Another approval that provides interesting insights into the use of retrospectively collected natural history data is that of defibrotide sodium (Defitelio) approved for the treatment of adult and pediatric patients with hepatic veno-occlusive disease (VOD) after hematopoietic stem-cell transplantation (HSCT), a rare disease with an 80% mortality rate and no available treatment options. The primary endpoint in the Defitelio pivotal study (survival at day 100) was compared to historical control data selected by independent retrospective review of patient records. Supportive data came from a dose-finding study, a compassionate use study, and a registry study. The major review issues pertained to the selection of the historical control group. The patients included in the historical control group were selected by a blinded, independent medical review committee who screened subjects undergoing HSCT. The committee used narratives, inclusion/exclusion case report forms, and partially redacted medical charts to select patients to be included in the control group. Although data collection for the treatment and historical control groups spanned vastly different timeframes (2 years and 12 years, respectively), the inclusion and exclusion criteria were pre-specified and were similar for both groups. The number of subjects in the historical control group was reduced (in two rounds) from 6867 to 123 and finally to 32 patients who had developed VOD and received standard of care. The last round was conducted after an interim efficacy analysis raised some concerns about bias because the survival rate in the larger historical control group initially selected was substantially higher than the rate generally reported in the literature. To adjust for the confounding effect of the potential prognostic factors, propensity score adjusted analyses were performed using four pre-specified covariates (all baseline prognostic factors of survival). Nonetheless, the day 100 survival rates of treated patients (38 to 45%) were higher than the historical control group (25%), the supportive care arm of the registry (31%), and published literature (< 20%). While FDA’s review included comments regarding the small size of the chosen historical control group and the risk of Type I error given the unplanned interim analyses, FDA ultimately approved Defitelio based on the totality and consistency of the data, particularly the consistency of the survival results in the pivotal study and supportive studies.

An example of a case using baseline control data for regulatory decision making is deferiprone (Ferriprox), an oral therapy for transfusional iron overload due to thalassemia syndrome (a rare disease). Deferoxamine, the only available therapy 15 at the time of Ferriprox’s new drug application (NDA) review, was not tolerated by all patients, leaving an unmet medical need. Initially, the sponsor received a complete response letter mainly due to uncertainty regarding the clinical meaningfulness of the change in a novel surrogate endpoint 16 in a single pivotal study versus deferoxamine. Ultimately, an independent committee selected a subset of patients (in whom previous chelation therapy was inadequate) from the sponsor’s previously conducted clinical studies, to be included in a prospectively planned study. This study compared the selected patients’ pre- and post-Ferriprox treatment results and showed that treatment with Ferriprox significantly decreased serum ferritin in about 50% of refractory patients. The statistical reviewer noted “this study has several serious limitations including lack of randomization, lack of control group, high rate of missing data and ignoring the variation between studies by simply pooling, all of which can introduce biases to the primary outcome.” Nevertheless, FDA considered the use of a prospectively planned statistical analysis plan and the selection of patients by the independent committee allowed an adequate selection of patients for the trial, minimized the possibility of bias, and allowed for an adequate assessment of drug effect. The review documents noted “This trial can be considered an adequate and well-controlled trial under the CFR and ICH E10 guidance for regulatory purposes.” Ferriprox was approved under the accelerated approval regulations.

An unusual use of a historical control that leveraged data from previously conducted clinical studies, was the addition of a new indication (monotherapy in patients with partial seizures) for lamotrigine extended release tablets (Lamictal XR) which was reviewed at an advisory committee meeting. 17 The supplemental NDA was based on a single study in which 223 patients who received one of two-dose levels were compared to a historical control group based on a retrospective analysis of control arms from eight studies previously conducted for other anti-epileptic products [18]. The sponsor considered use of placebo or pseudo-placebo controls unethical given the significant control data already available from previously conducted studies. At the advisory meeting, FDA presented a systematic evaluation of the key statistical issues based on the Pocock criteria [19], which were applicable to this situation, as the historical control data were specifically derived from the control arm from prior studies with similar designs and methods. This evaluation included the timeframe for assessment of seizure frequency and severity, how exit rate was calculated, medications at baseline, and regional differences between study and historical controls. The advisory committee agreed (14 yes/0 no) that the proposed historical control approach was acceptable in this specific circumstance. FDA’s presentations and discussions at the advisory committee demonstrate the importance of proactively assessing the comparability of an external control to the treatment group across multiple parameters and ensuring that endpoint evaluations and statistical methods address potential biases as thoroughly as possible. This precedent for use of historical controls from previously conducted clinical studies was later applied to other antiepileptic drugs, including lacosamide (Vimpat).

Finally, the recombinant antihemophilic factor Novoeight is an example where historical control data from nine publications were used as external controls to support its approval for prophylactic treatment of Hemophilia A, a rare disease. In this case, annualized bleeding rate (ABR) in patients treated prophylactically with Novoeight was compared with the ABR observed in historical controls treated with on-demand regimens. The historical ABR was calculated using data weighted by the number of patients in each of the nine published studies. Calculated mean ABR was 22 bleeds per patient per year for historical controls treated with on-demand regimens compared to 6.9 bleeds per patient per year in subjects treated with prophylactic Novoeight, a 68% reduction in bleeding rate for subjects treated with Novoeight prophylaxis as compared to on-demand therapy historical controls. This was considered acceptable for the approval of Novoeight for routine prophylaxis treatment.

Statistical and Methodological Considerations When Using External Controls

It is outside the scope of this article to provide a comprehensive review of methodological and statistical topics pertaining to the use of external controls, but some important considerations are highlighted in this section.

A key challenge of using external controls is that differences in prognostic variables (such as demographics, diagnostic criteria, disease stage, baseline status, and concomitant therapies) between the treated and external control groups could lead to biases particularly in the absence of randomization. One way of addressing bias is through proper selection of the external control group. Pocock proposed six criteria for a historical control group to be acceptable [19] (Fig. ​ (Fig.4), 4 ), sometimes cited by FDA reviewers, as in the previously mentioned Lamictal XR example. However, Pocock specifically intended these criteria (deemed stringent by Lim et al. [20]) for specialized methods for combining a historical control group from a previous trial with a randomized concurrent control group. Indeed, Pocock’s use of the term “historical control” differs from his contemporaries [21, 22], and from current usage in reference to non-concurrent external controls in general (a historical control per ICH E10 guidance is any “well-documented population of patients observed at an earlier time”) [1]. Thus, while the Pocock criteria may not all be applicable in a given situation, those that are should be applied to the extent possible in the selection of a historical control group and to the ensuing comparative statistical analyses [23].