Acromegaly is a disease caused by excess growth hormone production resulting in not only enlargement of hands, feet, forehead, jaw and nose but also multiple complications including diabetes, and premature death.
Treatment goals in acromegaly focus on lowering two hormones, principally insulin-like growth factor 1 (IGF-1) and also growth hormone (GH) to normal levels in the blood. With respect to early death and development of complications, normal levels of IGF-1 have been shown to be more desirable than high levels in acromegaly, however the wide range of normal values mean that prognosis can be difficult to calculate.
This study will examine firstly whether the relationship between normal and high IGF-1 and death in acromegaly reported in other populations can be detected in UK patients and if so, then secondly explore whether this relationship can be described in more detail across the distribution of IGF-1 values.
Although acromegaly is a rare disease (affecting about 6 in every 100,000 people), the CPRD database appears to hold records on sufficient patients with acromegaly to make the main aim of the study statistically feasible.
The study will combine health record data from both general practice and hospital admissions to reduce possible missing data and allow some of complexity between treatments for acromegaly and health outcomes to be understood.
In addition to death, the study will also explore whether different IGF-1 levels can predict other patient important outcomes such as new cardiovascular disease, diabetes, and cancer.
Acromegaly is caused by hypersecretion of growth hormone (GH) stimulating excess production of insulin-like growth factor 1 (IGF-1), mediating the somatic and metabolic features of the disease including somatic overgrowth, multiple comorbidities, premature mortality, and physical disfigurement.
Acromegalic patients are at risk of doubled mortality versus the general population, for which elevated rates of diabetes, hypertension, cardiovascular & respiratory disease, and some malignancies are contributory.
Routine measurement of IGF-1 is recommended in not only supporting the diagnosis of acromegaly but also as a biochemical target goal signifying disease control, however, there is a lack of consensus for target IGF-1 levels that correlate with either reduction in mortality risk or prevention of co-morbidities.
This study will describe the association between IGF-1 and all-cause mortality (ACM) in patients with acromegaly, determining not only the statistical shape of this relationship but also elucidating effect-modifiers of this relationship insofar as they are observable from the available clinical record.
Data from primary care will be linked to that from hospital admissions, cancer & death registrations to accurately determine exposures, outcomes, and co-variates. The primary hypothesis (association of raised IGF-1 level with all-cause mortality in acromegaly) will be tested using extended Cox proportional hazards regression modelling for post-index time-dependent effect modifiers related to acromegaly treatment. Restricted cubic spline functions will be applied to investigate not only the non-linear effects of continuous covariates but also of time-by-covariate interactions
The study outputs may help clinicians may be better able to make individualised treatment decisions relating to biochemical control in their patients with acromegaly and provide more accurate prognoses.
All-cause mortality (primary); incident cardiovascular disease (secondary); incident cancer (secondary); incident site-specific cancers (secondary); and incident diabetes (secondary).
Craig Currie - Chief Investigator - Cardiff University
Chris D Poole - Corresponding Applicant - Digital Health Labs Limited
Aled Rees - Collaborator - Cardiff University
Bethan Jones - Collaborator - Pharmatelligence Limited t/a Human Data Sciences
Jack Brownrigg - Collaborator - Pfizer Ltd - UK
John Ayuk - Collaborator - Queen Elizabeth Hospital
Sara Jenkins-Jones - Collaborator - Pharmatelligence Limited t/a Human Data Sciences
Sarah Wensley - Collaborator - Pfizer Ltd - UK
Thomas Berni - Collaborator - Pharmatelligence Limited t/a Human Data Sciences
Bethan Jones - Collaborator - Pharmatelligence Limited t/a Human Data Sciences
Jack Brownrigg - Collaborator - Pfizer Ltd - UK
Sara Jenkins-Jones - Collaborator - Pharmatelligence Limited t/a Human Data Sciences
Thomas Berni - Collaborator - Pharmatelligence Limited t/a Human Data Sciences
HES Admitted Patient Care;ONS Death Registration Data;Patient Level Index of Multiple Deprivation