A data-driven pipeline to extract potential adverse drug reactions through prescription, procedures and medical diagnoses analysis: application to a cohort study of 2,010 patients taking hydroxychloroquine with an 11-year follow-up

Context

Real-life data consist of exhaustive data which are not subject to selection bias. These data enable to study drug-safety profiles but are underused because of their temporality, necessitating complex models (i.e., safety depends on the dose, timing, and duration of treatment). We aimed to create a data-driven pipeline strategy that manages the complex temporality of real-life data to highlight the safety profile of a given drug.

Methods

We proposed to apply the weighted cumulative exposure (WCE) statistical model to all health events occurring after a drug introduction (in this paper HCQ) and performed bootstrap to select relevant diagnoses, drugs and interventions which could reflect an adverse drug reactions (ADRs). We applied this data-driven pipeline on a French national medico-administrative database to extract the safety profile of hydroxychloroquine (HCQ) from a cohort of 2,010 patients.

Results

The proposed method selected eight drugs (metopimazine, anethole trithione, tropicamide, alendronic acid & colecalciferol, hydrocortisone, chlormadinone, valsartan and tixocortol), twelve procedures (six ophthalmic procedures, two dental procedures, two skin lesions procedures and osteodensitometry procedure) and two medical diagnoses (systemic lupus erythematous, unspecified and discoid lupus erythematous) to be significantly associated with HCQ exposure.

Conclusion

We provide a method extracting the broad spectrum of diagnoses, drugs and interventions associated to any given drug, potentially highlighting ADRs. Applied to hydroxychloroquine, this method extracted among others already known ADRs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-022-01628-3.

• The challenge of drug-safety signal detection methods is to handle four types of difficulties:

○ The data source, the study of long-term adverse drug reactions or effects not suspected by healthcare professionals, requires the use of a real-life data source.

○ The consideration of a broad spectrum of potential adverse drug reactions (ADRs), and not only candidate ADRs.

○ The temporal impact (meaning that safety depends on the dose, date and duration of treatment).

○ The difference between true ADRs and disease natural course.

• We aimed to create a data-driven pipeline strategy, without any assumption of any ADRs, which take into account the complex temporality of real-life data to provide the safety profile of a given drug.

• Our pipeline used three sources of real-life data to establish a safety profile of a given drug: drug prescriptions, procedures and medical diagnoses.

• We successfully applied our data-driven pipeline strategy to hydroxychloroquine (HCQ). Our pipeline enabled us to find diagnoses, drugs and interventions related to HCQ and which could reflect an ADR due to HCQ or the disease itself.

• This data-driven pipeline strategy may be of interest to other experts involved in the pharmacovigilance discipline.

Evaluation of the peritoneal carcinomatosis index with CT and MRI

BACKGROUND

The aim was to determine the incremental value of MRI compared with CT in the preoperative estimation of the peritoneal carcinomatosis index (PCI).

METHODS

CT and MRI examinations of patients with peritoneal carcinomatosis were evaluated. CT images were first analysed by two observers who determined a first PCI (PCI_CT ). Then, the two observers reviewed MRI examinations in combination with CT and determined a second PCI (PCI_CT+MRI ). The sensitivity and negative predictive value of the two imaging sets were determined using surgery as a reference standard (PCI_Ref ).

RESULTS

CT plus MRI was more accurate in predicting the surgical PCI than CT alone. The absolute difference between PCI_CT+MRI and PCI_Ref was lower than that between PCI_CT and PCI_Ref (mean(s.d.) 3·96(4·10) versus 4·89(4·73); P = 0·010). The number of true-positive findings increased from 106 to 125 for reader 1 and from 117 to 132 for reader 2 with the adjunct of MRI. For both readers, an increased sensitivity was obtained when both MRI and CT were used (from 63 to 81 per cent for reader 1; from 44 to 81 per cent for reader 2). The increase in sensitivity was greater for patients with a moderate volume of disease.

CONCLUSION

The combination of CT and MRI improved the preoperative estimation of PCI compared with CT alone.

Perceived usefulness of nine quality improvement tools among Swiss physicians

BACKGROUND

Doctors' opinions about quality improvement tools likely influence their uptake and eventual impact on patient care. Little is known about physicians' perception of the comparative utility of various quality improvement tools.

METHODS

We conducted a mail survey of doctors in Geneva, Switzerland (2745 physicians, of whom 56% participated), to measure the perceived usefulness of 9 quality improvement tools.

RESULTS

In decreasing order of perceived utility these tools were regular continuous education (rated as very or extremely useful by 75% of respondents), mortality and morbidity conferences (65%), quality circles (60%), patient satisfaction measurement (42%), assessment of the fulfillment of therapeutic objectives (41%), assessment of compliance with guidelines (36%), periodic evaluation of doctors' skills (14%), onsite visits with peer-review of medical records (11%), and certification of office practices (8%).

CONCLUSION

Quality improvement tools seen as most useful by physicians are traditional methods such as continuous education and mortality and morbidity conferences. Methods that rely on the measurement of indicators or that have a judgmental component received less support.

Random modelling of contagious diseases

Modelling contagious diseases needs to include a mechanistic knowledge about contacts between hosts and pathogens as specific as possible, e.g., by incorporating in the model information about social networks through which the disease spreads. The unknown part concerning the contact mechanism can be modelled using a stochastic approach. For that purpose, we revisit SIR models by introducing first a microscopic stochastic version of the contacts between individuals of different populations (namely Susceptible, Infective and Recovering), then by adding a random perturbation in the vicinity of the endemic fixed point of the SIR model and eventually by introducing the definition of various types of random social networks. We propose as example of application to contagious diseases the HIV, and we show that a micro-simulation of individual based modelling (IBM) type can reproduce the current stable incidence of the HIV epidemic in a population of HIV-positive men having sex with men (MSM).