Volume 222 - Issue 1
The equitable challenges to quality use of modulators for cystic fibrosis in Australia
Authors: Laura K Fawcett, Shafagh A Waters and Adam Jaffe
Med J Aust 2025 || doi: 10.5694/mja2.52527
Published online: 2 December 2024
Published online: 2 December 2024
New pathways to address current inequities in Australian cystic fibrosis patients’ access to disease-modifying treatments, including in vitro cell models.
Cystic fibrosis, an autosomal recessive disease, causes premature mortality with a current life expectancy of 56 years.1 Variations in a single gene encoding the cystic fibrosis transmembrane conductance regulator (CFTR), an anion channel, cause this multisystemic disease.2 Bronchiectasis remains the most significant contributor to mortality, with other affected systems including the gastrointestinal, pancreatic, hepatobiliary, sweat glands and reproductive systems.3 Clinical manifestations of cystic fibrosis vary widely, leading to diverse phenotypic expressions.
Over 2000 CFTR variants have been described worldwide, with 719 confirmed as disease causing.4 These pathogenic variants are classified based on their functional consequence on the CFTR protein2 (Box 1). Class II includes F508del, the most prevalent CFTR variant globally.2 In Australia, about 90% of people with cystic fibrosis have at least one copy and about 50% are homozygous for the F508del allele.2,5
Therapeutic management of cystic fibrosis has evolved significantly over the past century. Aggressive early intervention with optimised nutrition, airway clearance and antibiotics, along with newborn screening and the introduction of specialist centres, increased the life expectancy from 4 to 40 years, but with a significant burden of care impacting quality of life.3 A landmark development occurred in 2011, 22 years after the CFTR gene was isolated, with the introduction of the first targeted disease modifying therapy, ivacaftor.2
Four CFTR modulators (ivacaftor, lumacaftor, tezacaftor and elexacaftor) have received approval from major regulatory bodies (Box 2). These approvals followed a development strategy with high throughput screening of 228000 compounds, using Fischer rat thyroid (FRT) cell lines and human bronchial epithelial cells.2 Drug candidates underwent animal toxicity studies and human clinical trials to ensure safety and efficacy. Ivacaftor functions as a CFTR channel potentiator.2 Lumacaftor and tezacaftor, first‐generation correctors, stabilise the CFTR protein to prevent premature degradation in the endoplasmic reticulum and are currently approved as dual combination medications with ivacaftor.2 The latest advancement is the triple combination therapy of two correctors, elexacaftor and tezacaftor, with ivacaftor (ETI), which is approved for people with cystic fibrosis with at least one F508del‐CFTR allele.6
The rarity of certain CFTR variants presents a challenge to large scale phase 3 clinical trials. To address this, in vitro data from FRT cell experiments were submitted to the American Food and Drugs Administration (FDA), leading to ivacaftor's extended approval and the establishment of a new precedent for drug approvals.2 Since then, the FDA has expanded the number of approved CFTR variants to 97 for ivacaftor, 127 for tezacaftor–ivacaftor and 177 for ETI, based on in vitro evidence and existing clinical data. In line with these developments, the Australian Therapeutic Goods Administration (TGA) has also expanded approvals.
In Australia, the TGA evaluates new drugs for safety, quality and efficacy, whereas the Pharmaceutical Benefits Advisory Committee recommends treatment subsidisation through the Pharmaceutical Benefits Scheme (PBS) ensuring eligible patients have affordable access. The details of TGA drug approvals and PBS listings can differ, with PBS listings often being more restrictive (Box 2).
The challenges
Inequitable access to CFTR modulators
The introduction of CFTR modulators has created inequity among people with cystic fibrosis, distinguishing between individuals eligible for CFTR modulators and individuals who are not. In Australia, about one‐third of people with cystic fibrosis have the choice of three modulators (Box 2). Australian people with cystic fibrosis who are ineligible for CFTR modulators are either too young, have CFTR variants unresponsive to modulators tested in FRT cells, have extremely rare CFTR variants not studied in vitro or included in clinical trials, or have an FDA but not TGA approved CFTR variant and would be eligible for ETI if they lived overseas.
Longstanding inequitable health outcomes in cystic fibrosis are similar to other chronic conditions; life expectancy is greater for people with cystic fibrosis in high income countries and for those with access to publicly funded health care.7,8 The introduction of CFTR modulators, with an annual public price exceeding $250000 per patient, has accentuated this gap, offering decades of additional life expectancy for people with cystic fibrosis in countries with access to these treatments.9 However, even within these countries, disparities exist due to socio‐economic status, race and ethnicity.10 The introduction of CFTR modulators adds a genetic factor to these disparities, with American cystic fibrosis registry data demonstrating that people with cystic fibrosis from ethnic minority groups have reduced access to CFTR modulators due to a higher rate of extremely rare ineligible CFTR variants.10
Heterogenous clinical response to CFTR modulators
Over 50% of phase 3 clinical trials of CFTR modulators used forced expiratory volume in 1 second (FEV1) as the primary endpoint (Box 3). A decline in FEV1, an indicator of the severity of cystic fibrosis lung disease, predicts the need for lung transplant or mortality within the next two years.11 However, FEV1 is insensitive to localised or early cystic fibrosis disease and may remain normal (>80% predicted) despite evidence of structural lung changes on computed tomography imaging.12 Therefore, other primary outcome measures have been used in clinical trials and include: the lung clearance index (LCI; a sensitive measure of ventilation inhomogeneity in small airways via multiple breath washout)3 and the Cystic Fibrosis Questionnaire‐Revised (CFQ‐R;13 a patient‐reported outcome measure of quality of life). The sweat chloride level, originally a diagnostic test for cystic fibrosis, now serves as a biomarker of CFTR function and is a routine secondary endpoint (Box 3).14
Traditional double blind placebo‐controlled trials typically use frequentist statistics to detect treatment effects at a group level. However, Boyle and colleagues demonstrated heterogenous responses between individuals with the same CFTR genotype, a finding echoed in later clinical trials of lumacaftor–ivacaftor, tezacaftor–ivacaftor and ETI.6,15 This highlights the limitation of grouped analyses, which may not fully capture the potential benefits for individual responders, thus underscoring the need for predictive tools to determine which individuals are most likely to benefit from which treatments.
Several hypotheses have been proposed to explain the observed heterogeneity in drug response. These include genetic variability in CYP450 enzymes involved in the metabolism of CFTR modulators and complex CFTR alleles (eg, F508del; L467F), which have been linked with non‐response to CFTR modulators in people with cystic fibrosis who would otherwise be expected to respond based on their F508del genotype.16
New CFTR modulators targeting patients already taking a CFTR modulator
As CFTR modulators continue to evolve, new investigational therapies must consider novel clinical trial designs to address existing effective therapies. GLPG1837, an alternative to ivacaftor, successfully navigated this challenge by implementing a one‐week washout period at the start of the study with no reported serious adverse events. However, there are reports of ivacaftor withdrawal syndrome, characterised by severe and sudden decline in lung function following three to four days of ivacaftor interruption, including one fatality.17 Although rare, ivacaftor withdrawal syndrome presents a significant ethical concern regarding cessation of modulator therapy for participants assigned to a placebo arm in classically designed randomised controlled trials (RCTs).
Following the establishment of lumacaftor–ivacaftor and tezacaftor–ivacaftor as the standard of care for F508del homozygous people with cystic fibrosis in the United States, ETI clinical trials used tezacaftor–ivacaftor as the comparator in relevant clinical trials, providing a direct comparison (elexacaftor–tezacaftor–ivacaftor versus tezacaftor–ivacaftor). However, lumacaftor–ivacaftor and tezacaftor–ivacaftor were only evaluated in separate placebo controlled RCTs. This translated to a challenge in clinical practice for those already taking lumacaftor–ivacaftor when tezacaftor–ivacaftor was approved, given the known heterogeneity in CFTR modulator response. Both modulators showed similar efficacy, with differences in adverse event and drug–drug interaction profiles. This problem continues to evolve with the development of new modulators; recently published phase 2 trial results of a new triple therapy compound targeting patients already eligible for ETI illustrates the urgent need for a solution to the problem.18
Proposed solutions
Adoption of in vitro cell models as companion diagnostics
In vitro cell models were instrumental in the development of CFTR modulators and the expansion of treatment approvals to rare CFTR variants. Among these models, two primary cell models (rectal organoids and human nasal epithelial cells grown at air liquid interface) have shown promise in predicting an individual's response to CFTR modulator treatments and are endorsed by the Australian cystic fibrosis community.19,20,21 The pan‐European initiative, HIT‐CF (human individualized therapy of cystic fibrosis), has used organoids from over 500 patients with rare CFTR variants to assess responses to CFTR modulators. The results will be used to screen patients for participation in clinical trials, preventing the enrolment of participants with non‐responsive variants.
The importance of using individual primary cell lines rather than immortalised cell lines was highlighted by the conflicting results between FRT and primary cell models for the rare G970R‐CFTR variant and the more common N1303K‐CFTR variant, with the primary cell models more accurately predicting the clinical response.22 Assumptions about the effect of G970R‐CFTR on mRNA splicing, resulted in an FRT model that did not accurately reflect the response in people with cystic fibrosis.23
Currently, the application of this technology remains constrained to research studies, hindered by the absence of standardisation and validation across different laboratories. Addressing this is critical if this technology is to be embedded in future health care for people with cystic fibrosis. Although global efforts to address standardisation are ongoing, individual laboratory standards and reference lines are established and meaningful interpretation of results is already possible. Primary cell organoids could be used to identify non‐responders and prevent people with cystic fibrosis receiving ineffective treatments, thereby avoiding low value health care.
Adaptive trials, n = 1 studies and broader inclusion of paediatric participants
Unlike traditional clinical trials, adaptive trials are designed to evolve based on ongoing data analysis during the trial itself. These trials can modify their parameters, such as sample size, randomisation allocation or add new treatment arms as new therapies are developed, allowing efficient exploration of multiple treatment options. n = 1 studies, which use the patient as their own control, can address the issue of small patient populations such as people with cystic fibrosis with rare CFTR variants. These innovative trial designs often use Bayesian statistics, which despite being challenging for many to comprehend and critique confidently, have been embraced by the FDA for evaluating treatments for rare diseases.24
CFTR modulator trials in children aged under 6 years have focused on safety and tolerability, with no control arms and small sample sizes (Box 3). This limits the ability to measure secondary outcomes of efficacy and the number of children able to access therapy. Greater inclusion of young children would address this, although we acknowledge the challenges in conducting paediatric clinical trials.45
Named patient and compassionate access to CFTR modulators
In Australia, there is currently no pathway for people with cystic fibrosis to access modulator treatment based on individual in vitro effectiveness data. Whereas, in New Zealand, people with cystic fibrosis with rare variants can apply for named patient access if they can demonstrate evidence of their variant's responsiveness to ETI. One way to demonstrate this might be by using their own organoids. However, cystic fibrosis laboratories conducting organoid research in the southern hemisphere are only based in Australia. We are also aware of an individual in England who has used the individual funding request pathway (National Health Service, England) to facilitate access to a CFTR modulator using their organoid data and reports from Israel of insurance cover providing access to patients based on in vitro data.
In 2022, French authorities facilitated compassionate access to ETI for people with cystic fibrosis with advanced lung disease who were not eligible for ETI. An observational study measured the effectiveness of ETI using several endpoints evaluated by consensus decision by a centralised committee.46 This approach identified 45 individuals (54% of participants) with a rapid, clinically significant response to ETI who were previously unable to access ETI due to their genotype. In addition, human nasal epithelial cell cultures from participants in the scheme were predictive of the individual's clinical response.19 Adapting this approach to an Australian setting would be relatively straightforward and could be extended to other precision medicine therapies.
Conclusion
Given the rapidly evolving landscape of precision medicine, the Australian health technology assessment pathway is undergoing its first review in over three decades. We eagerly await the outcomes and hope that new pathways will address current inequities in Australian cystic fibrosis patients’ access to disease‐modifying treatments. Incorporating in vitro cell models into cystic fibrosis care could identify the best therapy (in terms of CFTR rescue) for patients with multiple therapeutic options and help address inequity by providing access for patients with rare variants.
Box 1 – Cystic fibrosis transmembrane conductance regulator (
CF = cystic fibrosis; CFTR =cystic fibrosis transmembrane conductance regulator; F = F508del; WT = wildtype. Variants in classes I and II are considered minimal function (MF). Class I variants result in abnormal protein synthesis. Variants such as G542X and W1282X, result in premature termination codons with nonsense mediated decay resulting in no CFTR protein. It is estimated that 17.8% of Australian people with cystic fibrosis have an F508del(F)/MF genotype. Class II variants result in proteins with trafficking abnormalities. Class II includes F508del, the most prevalent CFTR variant in the cystic fibrosis population with 90% of people with cystic fibrosis having at least one copy of F508del and about 50% of people with cystic fibrosis being homozygous (F/F). Class III or Gating (G) variations describe a CFTR protein that reaches the cell surface but does not act as a channel due to dysfunctional gating, with G551D being the most prevalent example. Australian registry data indicates that 7.5% of people with cystic fibrosis have an F/G CFTR genotype. Residual function (RF) variants include classes IV, V and VI with 5.5% of Australian people with cystic fibrosis having a F/RF CFTR genotype. Class IV variants result in protein channels with reduced conductance so while anions can be transported, homeostasis is still disrupted, examples include R117H and D1152H. Class V variants have reduced levels of protein and include A455E and 2789+5G>A and class VI variants such as Q1411X result in less stable proteins. Residual function variants usually present with a milder cystic fibrosis phenotype or CFTR‐related disorder and have a longer life expectancy than people with cystic fibrosis with class I–III CFTR variants only.2,5 Figure made with biorender.
Box 2 – Eligibility criteria for cystic fibrosis transmembrane conductance regulator (CFTR) modulators in Australia
|
Modulator name |
Mechanism of action |
PBS approval criteria |
TGA approval criteria |
Approved age (PBS v TGA) |
Responsive variants* |
||||||||||
|
|
|||||||||||||||
|
Ivacaftor |
Potentiator |
|
|
>4 months (PBS and TGA) |
92 |
||||||||||
|
Lumacaftor–ivacaftor |
Type I corrector/potentiator |
|
|
>1 year (PBS and TGA) |
‐ |
||||||||||
|
Tezacaftor–ivacaftor |
Type I corrector/potentiator |
|
|
>12 years (PBS); >6 years (TGA) |
25 |
||||||||||
|
Elexacaftor–tezacaftor–ivacaftor (ETI) |
Type III corrector/type I corrector/potentiator |
F/any |
F/any |
>6 years (PBS); >2 years (TGA) |
‐ |
||||||||||
|
|
|||||||||||||||
|
PBS = Pharmaceutical Benefits Scheme; TGA = Therapeutic Goods Administration; F = F508del (example CFTR genotype); RF = residual function. * The “Responsive Variants” column lists the number of CFTR gene variants responsive to each modulator as recognised by the TGA, with the current count accurate as of June 2024. The number of responsive variants for ivacaftor and tezacaftor–ivacaftor can vary and should be verified against the latest TGA and PBS listings. |
|||||||||||||||
Box 3 – Summary of phase 3 trials for cystic fibrosis transmembrane conductance regulator (CFTR) modulators
|
Drug |
Publication |
RCT comparator |
Ages |
Variants |
Treatment duration |
n |
Primary outcome(s) |
Secondary/tertiary outcomes |
|||||||
|
|
|||||||||||||||
|
Ivacaftor |
Ramsey et al (2011)25 |
Placebo |
>12 years |
G551D |
24 weeks |
161 |
FEV1 |
CFQ‐R, FEV1, PEx, SwCl, weight, antibiotic use |
|||||||
|
Davies et al (2013)26 |
Placebo |
6–11 years |
G551D |
48 weeks |
52 |
FEV1 |
CFQ‐R, FEV1, SwCl, weight |
||||||||
|
Moss et al (2015)27 |
Placebo |
>6 years |
R117H |
24 weeks |
69 |
FEV1 |
BMI, CFQ‐R, PEx, SwCl |
||||||||
|
De Boeck et al (2014)28 |
Placebo crossover |
>6 years |
G1244E, G1349D, G178R, G551S, G970R, S1251N, S1255P, S549N, or S549R |
8 weeks |
39 |
FEV1 |
BMI, CFQ‐R, SwCl |
||||||||
|
Davies et al (2016)29 |
Open label |
2–5 years |
G551D, S549N |
24 weeks |
34 |
PK, Safety |
BMI, FEV1, faecal elastase, height, IRT, SwCl, weight |
||||||||
|
Rosenfeld et al (2018)30 |
Open label |
12–24 months |
G551D, S549N, G178R G551D, G178R, R117H‐5T |
24 weeks |
19 |
PK, Safety |
Faecal elastase, faecal calprotectin, growth, IRT, microbiology, palatability, PEx, SwCl |
||||||||
|
Davies et al (2021)31 |
Open label |
4–12 months |
G551D, G178R, R117H‐5T |
24 weeks |
17 |
PK, Safety |
Faecal elastase, faecal calprotectin, growth, IRT, LCI, SwCl |
||||||||
|
Lumacaftor–ivacaftor |
Wainright et al (2015)32 |
Placebo |
>12 years |
F/F |
24 weeks |
559 |
FEV1 |
BMI, CFQ‐R, FEV1, hospitalisations, IV Abx treatments, PEx, weight |
|||||||
|
Wainright et al (2015)32 |
Placebo |
>12 years |
F/F |
24 weeks |
563 |
FEV1 |
BMI, CFQ‐R, FEV1, hospitalisations, IV Abx treatments, PEx, weight, |
||||||||
|
Milla et al (2017)33 |
Open label |
6–11 years |
F/F |
24 weeks |
58 |
PK, Safety |
BMI, CFQ‐R, height, SwCl, TSQM, weight |
||||||||
|
Ratjen et al (2017)34 |
Placebo |
6–11 years |
F/F |
24 weeks |
206 |
LCI |
BMI, CFQ‐R, FEV1, height, PEx, SwCl, TSQM, weight |
||||||||
|
McNamara et al (2019)35 |
Open label |
2–5 years |
F/F |
24 weeks |
60 |
PK, Safety |
BMI, faecal elastase, FEV1, height, IRT, LCI, microbiology, PEx, SwCl, weight |
||||||||
|
Rayment et al (2022)36 |
Open label |
1–2 years |
F/F |
24 weeks |
46 |
PK, Safety |
BMI, faecal elastase, faecal calprotectin height, IRT, PEx, SwCl, weight |
||||||||
|
Tezacaftor–ivacaftor |
Taylor‐Cousar et al (2017)37 |
Placebo |
>12 years |
F/F |
24 weeks |
510 |
FEV1 |
BMI, CFQ‐R, FEV1, PEx, SwCl |
|||||||
|
Rowe et al (2017)38 |
Ivacaftor or placebo (crossover + washout) |
>12 years |
F/predicted responsive ivacaftor variant |
8 weeks |
248 |
FEV1 |
BMI. CFQ‐R, faecal elastase, IRT, PEx, SwCl |
||||||||
|
Walker et al (2019)39 |
Open label |
6–11 years |
F/F or F/RF |
24 weeks |
70 |
PK, Safety |
BMI, CFQ‐R, FEV1, height, SwCl, weight |
||||||||
|
Elexacaftor–tezacaftor–ivacaftor |
Middleton et al (2019)6 |
Placebo |
>12 years |
F/MF |
24 weeks |
405 |
FEV1 |
BMI, CFQ‐R, FEV1, PEx, SwCl |
|||||||
|
Hejjerman et al (2019)40 |
Tezacaftor–ivacaftor |
>12 years |
F/F |
4 weeks |
113 |
FEV1 |
CFQ‐R, SwCl |
||||||||
|
Sutharsan et al (2022)41 |
Tezacaftor–ivacaftor |
>12 years |
F/F |
24 weeks |
175 |
CFQ‐R |
BMI, FEV1, height, SwCl, weight |
||||||||
|
Zemanick et al (2021)42 |
Open label |
6–11 years |
F/F or F/MF |
24 weeks |
66 |
PK, Safety |
BMI, CFQ‐R, FEV1, height, LCI, PEx, SwCL, weight |
||||||||
|
Mall et al (2022)43 |
Placebo |
6–11 years |
F/MF |
24 weeks |
121 |
LCI |
CFQ‐R, FEV1, SwCl, Safety and tolerability |
||||||||
|
Goralski et al (2023)44 |
Open label |
2–5 years |
F/any |
24 weeks |
75 |
PK, Safety |
BMI, faecal elastase, faecal calprotectin, height, IRT, LCI, PEx, SwCl, weight |
||||||||
|
|
|||||||||||||||
|
BMI = body mass index; CFQ‐R = Cystic Fibrosis Questionnaire‐Revised; F = F508del (example CFTR genotype); FEV1 = forced expiratory volume in 1 second; IRT = immunoreactive trypsinogen; IV Abx = intravenous antibiotic use; LCI = Lung Clearance Index; MF = minimal function; PK = pharmacokinetics; PEx = pulmonary exacerbation data; RCT = randomised controlled trial; RF = residual function; SwCl = sweat chloride; TSQM = Treatment Satisfaction Questionnaire for Medication. Where an endpoint is listed as both primary and secondary/tertiary endpoint, multiple time points were evaluated during the study. Where studies included two parts, the treatment duration reflects the longest duration for the primary endpoint in the trial. All studies collected safety data. |
|||||||||||||||
Competing interests
AJ is chair of the scientific and medical advisory committee of Rare Voices Australia and has received speaker payments from Vertex Pharmaceuticals. LF has been a sub‐investigator on Vertex clinical trials and received sponsorship of travel costs to attend educational meetings. SW has received competitive funding sponsored by Vertex Pharmaceuticals. Vertex Pharmaceuticals had no involvement in the planning, writing or publication of this article.
Acknowledgements
LF is supported by the Rotary Club of Sydney Cove/Sydney Children's Hospital Foundation and UNSW postgraduate award scholarships. SW is supported by the UNSW Scientia program and the Australian National Health and Medical Research Council. There was no role of the funding sources in the planning, writing or publication of the work. Colman Taylor provided feedback on a draft manuscript regarding health technology assessment pathways.
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Provenance: Not commissioned; externally peer reviewed.