Open access Protocol BMJ Open: first published as 10.1136/bmjopen-2019-033659 on 28 April 2020. Downloaded from http://bmjopen.bmj.com/ on October 20, 2023 at Univesity Autonomous of Barcelona. Rationale and methodology for a European pooled analysis of postmarketing interventional and observational studies of insulin glargine 300 U/mL in diabetes: protocol of REALI project Nick Freemantle,1 Riccardo C Bonadonna,2,3 Pierre Gourdy,4,5 Didac Mauricio ‍ ‍,6,7 Dirk Mueller-­Wieland,8 Gregory Bigot,9 Alice Ciocca,10 Celine Mauquoi,11 Mélissa Rollot,12 Mireille Bonnemaire10 To cite: Freemantle N, Abstract Bonadonna RC, Gourdy P, et al. Strengths and limitations of this study Introduction Type 2 diabetes mellitus (T2DM) is a Rationale and methodology for common and heterogeneous disease. Using advanced a European pooled analysis of ►► The large European sample size allows more precise analytic approaches to explore real-­world data may postmarketing interventional statistical calculations and provides European clini- identify different disease characteristics, responses to and observational studies cians with findings relevant to their specific patient Protected by copyright. of insulin glargine 300 U/ treatment and progression patterns. Insulin glargine 300 populations. mL in diabetes: protocol of units/mL (Gla-300) is a second-­generation basal insulin ►► The mixture of interventional and observational REALI project. BMJ Open analogue with preserved glucose-­lowering efficacy but studies including information from a wider patient 2020;10:e033659. doi:10.1136/ reduced risk of hypoglycaemia. The purpose of the REALI population, such as the elderly or those with co- bmjopen-2019-033659 pooled analysis described in this paper is to advance the morbidities (who might normally be omitted from understanding of the effectiveness and real-­world safety ►► Prepublication history for premarketing clinical trials), creates a valuable real-­ this paper is available online. of Gla-300 based on a large European patient database of world data set. To view these files, please visit postmarketing interventional and observational studies. ►► Bias(es) may exist in some data due to greater rep- the journal online (http://​dx.​doi.​ Methods and analysis In the current round of pooling, resentation of certain countries and/or between-­ org/​10.​1136/​bmjopen-​2019-​ REALI will include data from up to 10 000 subjects with study differences in the management of patients. 033659). diabetes mellitus (mostly T2DM) from 20 European ►► The power of the extensive sample size of the REALI countries. Outcomes of interest include change from Received 15 August 2019 project may be reduced in certain patient profiles baseline to week 24 in haemoglobin A1c, fasting plasma Revised 29 February 2020 because some data (eg, specific laboratory values glucose, self-­measured plasma glucose, body weight, Accepted 23 March 2020 or patient-­reported outcomes) were not collected in insulin dose, incidence and rate of any-­time-­of-­the-­day all studies. and nocturnal hypoglycaemia. The data pool is being ►► The REALI project could function as a blueprint for investigated using two complementary methodologies: further evaluation of new treatment strategies aim- a conventional descriptive, univariate and multivariable ing to identify markers to optimise the treatment of prognostic analysis; and a data-­mining approach using each patient and to recognise respective clinical subgroup discovery to identify phenotypic clusters of subgroups. patients who are highly associated with the outcome of interest. By mid-2019, deidentified data of 7584 patients were included in the REALI database, with a further Introduction expected increase in patient number in 2020 as a result of Diabetes mellitus (DM) is a heterogeneous pooling additional studies. © Author(s) (or their disease, with a population that exhibits employer(s)) 2020. Re-­use Ethics and dissemination The proposed study does not involve collection of primary data. Moreover, all individual diverse clinical and biological characteris- permitted under CC BY-­NC. No commercial re-­use. See rights study protocols were approved by independent local tics.1 2 Current American Diabetes Associa- and permissions. Published by ethics committees, and all study participants provided tion (ADA) and European Association for BMJ. written informed consent. Furthermore, patient data is the Study of Diabetes (EASD) guidelines For numbered affiliations see deidentified before inclusion in the REALI database. Hence, recommend a patient-­centred approach that end of article. there is no requirement for ethical approval. Results will takes into account individual patient pref- be disseminated via peer-­reviewed publications and erences and needs.3 4 Indeed, it has been Correspondence to presentations at international congresses as data are shown that in addition to pharmacogenetic Nick Freemantle; analysed. ​nicholas.​freemantle@​ucl.​ac.u​ k factors, phenotypic and clinical features, Freemantle N, et al. BMJ Open 2020;10:e033659. doi:10.1136/bmjopen-2019-033659 1 Open access BMJ Open: first published as 10.1136/bmjopen-2019-033659 on 28 April 2020. Downloaded from http://bmjopen.bmj.com/ on October 20, 2023 at Univesity Autonomous of Barcelona. such as body weight, age of diabetes onset and comor- treatment.19 Specifically, combining and analysing Euro- bidities, may influence the outcomes of glucose-­lowering pean data from different observational and interven- therapies.1 5 6 Moreover, it is also recommended to have tional studies would increase the precision with which to tailored glycaemic targets for each patient.7 Hence, to describe the overall treatment effect of Gla-300 and would individualise treatments and glycaemic targets appropri- be useful to compare clinical outcomes in various subpop- ately, it is important to assess treatment effectiveness in ulations of interest that may be less represented in RCTs different patient profiles to ensure patients receive the (eg, patients with renal impairment, older adults, patients interventions that are most likely to provide the greatest a thigh risk of hypoglycaemia, etc). In the present paper, benefit. the rationale and methodology of the REALI project, The most recent ADA/EASD recommendations recog- which is an ongoing incremental data pooling initiative nise the need for basal insulin, with low risk of hypogly- including postmarketing interventional and observa- caemia or weight gain, in the treatment of patients with tional studies of Gla-300 in different real-­world settings type 2 diabetes mellitus (T2DM).4 Insulin glargine 300 across Europe, is reported. units/mL (Gla-300) is a second-­generation basal insulin analogue with a more stable and prolonged pharmaco- kinetic/pharmacodynamic profile than insulin glargine Methods and analysis 100 units/mL (Gla-100) that lasts beyond 24 hours.8 9 It Overall project design was approved in 2015 by both the United States Food The REALI project will create a pooled database that and Drug Administration and the European Medicines combines data from more than 16 studies covering Agency for the treatment of type 1 diabetes mellitus 20 European countries, and will comprise real-­ world (T1DM) and T2DM.8 10 The efficacy and safety of Gla-300 data from over 10 000 patients with T1DM or T2DM compared with Gla-100 has been investigated in several who were initiated on Gla-300, or switched from other randomised controlled trials (RCTs), including the glucose-­lowering therapies to Gla-300, due to unsatisfac- EDITION Phase III clinical trial programme, which tory glycaemic control. The data set used for the REALI comprised a series of international, multicentre, treat-­to-­ project consists of a mixture of information generated target RCTs conducted in distinct populations of patients from both interventional (single-­arm or multiarm) and Protected by copyright. with T1DM or T2DM.11 12 The EDITION studies demon- observational studies conducted in the postmarketing strated comparable reductions in haemoglobin A1c setting. (HbA1c) levels, but with less hypoglycaemia with Gla-300 The REALI project extracts information from each compared with Gla-100 in people with T2DM12 13 and study on characteristics (ie, baseline information and rele- T1DM,11 irrespective of a patient’s age, body mass index vant effectiveness and safety parameters) that constitute (BMI), age at onset of DM or duration of DM. the minimum required variables common to all studies While RCTs are generally considered the gold standard included in this database. All other patient-­level variables for evaluating the effects of drugs in specific disease and are also captured in the REALI database. Study-­level char- patient settings, it is often challenging to extrapolate acteristics (design, country and follow-­ up length) are their results to more general patient populations in real-­ also extracted from each trial included in the data set. life clinical circumstances.14 Real-­world evidence (RWE), Once a study has been conducted, a case report form, resulting from the rigorous analysis of diverse sources of which includes details about the variables of interest, is data, including electronic health records, claims data, collected. The study’s database is then cleaned and locked, disease registries and data from personal devices/software and subsequently made available to the country of origin applications, is an important complementary component for local statistical analysis, while being sent simultane- to clinical trial data as it provides a broader and unique ously for central deidentification. Following this process, insight into patient information, which could improve the data added to the REALI database are mapped and clinical decision-­ making in DM management.14 Real-­ pooled into a common database for statistical analysis. world studies conducted in large T2DM patient popula- Figure 1 illustrates the overall REALI project design. tions in the USA, such as the DELIVER D+,15 DELIVER All studies included in the database were conducted 216 and the LIGHTNING17 studies, provide complemen- according to Good Clinical Practice and the Declaration tary findings that support results from RCTs and reflect of Helsinki. Ethical approval was obtained for each study the effectiveness of Gla-300 in real-­world clinical prac- and all participants provided written informed consent. tice. Similarly, in Europe where daily clinical practice may differ from the USA, a number of postmarketing Patient population interventional, observational and RWE studies are being Studies include adult patients (≥18 years of age) with a conducted to assess the effectiveness and safety profile of confirmed diagnosis of T1DM or T2DM who initiated Gla-300 under real-­life daily clinical practice conditions.18 Gla-300 and were uncontrolled on their previous glucose-­ Summary statistics, such as those derived from system- lowering treatments. The minimum treatment duration atic reviews and pooled data analyses, are important required for the REALI studies is 24 weeks (6 months) of tools to discover further novel insights and to guide clin- Gla-300 therapy, with at least two study visits: at baseline ical thinking, practice, education and research in DM and at week 24. Although both T1DM and T2DM patients 2 Freemantle N, et al. BMJ Open 2020;10:e033659. doi:10.1136/bmjopen-2019-033659 Open access BMJ Open: first published as 10.1136/bmjopen-2019-033659 on 28 April 2020. Downloaded from http://bmjopen.bmj.com/ on October 20, 2023 at Univesity Autonomous of Barcelona. Additional outcome measures, which are collected in only some studies, include patient-­ reported outcomes, low-­density lipoprotein cholesterol, estimated glomerular filtration rate (eGFR) and vital signs at baseline and week 24. Data that were requested in certain studies but were not collected will be described as ‘missing data’, whereas those that were not requested will be described as ‘unavailable data’. Statistical analyses Figure 1 Project design of REALI. CRF, case report form; The overall population comprises all patients who are CRO, contract research organisation; EU, European Union. identified in the locked individual databases as having entered a study, while the treated population includes all patients who are identified as having entered a study in are included in REALI, the majority of patients have addition to having been treated with at least one reported T2DM. For insulin-­ naïve patients with T2DM, uncon- injection of Gla-300 within the individual study period. trolled on oral glucose-­lowering therapy, Gla-300 is added To enhance the informative output of the pooled data- with or without adjustment of their previous treatment(s), base, the REALI project uses two statistical methodolog- whereas patients with T1DM and T2DM pretreated with ical approaches: a conventional descriptive and modelling basal insulin are switched to Gla-300 treatment. There analysis, and a subgroup discovery approach. are no restrictions on the number of previous glucose‐ The conventional descriptive analyses assess patient lowering therapies. The inclusion and exclusion criteria characteristics and clinical effectiveness and safety for each individual Gla-300 study are defined in the corre- outcomes in the overall population as well as in patient sponding country’s clinical study protocol. In all obser- subgroups of interest such as the following: ►► Insulin-­naïve versus insulin-­pretreated patients. Protected by copyright. vational and most interventional studies, the inclusion 2 ►► Patients with eGFR <60 mL/min/1.73 m versus criteria have been broadly defined to allow for inclusion 2 of any patient who would benefit from Gla-300 insulin ≥60 mL/min/1.73 m . ►► Patients <65 years of age versus those between 65 and therapy to improve diabetic control. 75 years versus ≥75 years. ►► Early-­ onset versus late-­onset diabetic patients, based Outcomes on age threshold. Studies are included in the REALI database if they report Moreover, this approach allows for comparisons on the following demographic and clinical characteris- between interventional and observational studies. For the tics at baseline: age, gender, BMI, comorbidities, disease conventional descriptive approach, data will be analysed characteristics such as type and duration of diabetes, and at the patient level. Descriptive subgroup analyses by age, previous and concomitant therapies. eGFR, gender and insulin pretreatment status are being With respect to the effectiveness of Gla-300 therapy, the conducted. Univariate and multivariable analyses are outcomes of interest, related to glycaemic control, are as being performed to identify potential factors that predict follows: improved glycaemic control as well as adverse events, ►► HbA1c(%) change from baseline to week 24. such as baseline BMI evaluated as a continuous variable ►► Proportion of patients achieving HbA1c targets (using a linear function). Further statistical methods may (<7.0% and <7.5%) at week 24. be considered as the project evolves and will be defined ►► Fasting plasma glucose (mg/dL) change from base- in the statistical analysis plan. line to week 24. The subgroup discovery approach is a broadly appli- ►► Self-­measured plasma glucose (mg/dL) change from cable data-­mining technique that aims to discern clus- baseline to week 24. ters of patients with more favourable or less favourable Safety endpoints include the following: glycaemic outcomes and who, therefore, may benefit ►► Overall safety of Gla-300: frequency and type of the most or the least from Gla-300, without pre-­existing adverse events and serious adverse events. hypotheses.21 This tool generates data-­driven hypotheses, ►► Incidence and event rates of hypoglycaemia defined which may confirm existing hypotheses or facts relating according to the ADA classification20 and by time of day to Gla-300 efficacy and safety and/or may be novel empir- (any-­time-­of-­the-­day and nocturnal hypoglycaemia). ical hypotheses to increase understanding of treatment Other outcomes that are collected in all included response. For the subgroup discovery approach, Q-­Finder studies consist of the following: (Quinten, Paris, France), a proprietary non-­parametric ►► Body weight (kg) change from baseline to week 24. supervised learning algorithm working with no partic- ►► Change in Gla-300 daily dose (U/kg/day) from base- ular assumption regarding distributions of outcomes line to week 24. or explanatory variables, will be used to generate new Freemantle N, et al. BMJ Open 2020;10:e033659. doi:10.1136/bmjopen-2019-033659 3 Open access BMJ Open: first published as 10.1136/bmjopen-2019-033659 on 28 April 2020. Downloaded from http://bmjopen.bmj.com/ on October 20, 2023 at Univesity Autonomous of Barcelona. need of basal insulin therapy. The large REALI database is being explored using two different statistical methods to investigate the profiles of patients whose glycaemic control is improved in varying degrees after initiation of Gla-300 treatment. At the time of writing this paper, data from 7584 patients are being included in the REALI data pool, and this number is set to grow further as shown in table 1. Pooled data analyses have previously been conducted Figure 2 Q-­Finder methodology. BL, baseline; BMI, to inform treatment options for T2DM. A 2011 pooled body mass index; FPG, fasting plasma glucose; HbA1c, analysis of 38 phase II and phase III studies evaluated the haemoglobin A1c; SBP, systolic blood pressure; T2DM, type 2 safety and tolerability of the dipeptidyl peptidase-4 inhib- diabetes mellitus. itor vildagliptin, administered as a monotherapy or in combination with metformin, thiazolidinediones, sulfo- nylureas or insulin for ≥12 weeks up to 2 years in patients empirical hypotheses and produce patient profiles of with T2DM.24 Moreover, a recent posthoc pooled analysis, good responders to Gla-300.22 23 In this respect, the raw of three pivotal RCTs in adult patients with T2DM using data from the interventional and observational studies only basal insulin (EDITION 2, EDITION 3 and EDITION are first checked for consistency, and only patients with JP 2), was conducted to evaluate the risk of nocturnal available HbA1c values at baseline and week 24 from the hypoglycaemia with Gla-300 versus Gla-100. This pooled pooled database are included. This information is then analysis found a lower incidence of nocturnal hypogly- flattened from one row of data per patient per visit, to one caemia with Gla-300 versus Gla-100, which was confirmed row per patient and one column per visit. Next, the data using all analysed time windows, showing a consistently are consolidated into a learning matrix, which includes reduced risk with Gla-300 compared with Gla-100.25 Simi- the outcome and patient baseline characteristic values. larly, a 2013 pooled analysis of 24-­week data, from nine Three learning matrices are produced: one for learning prospective, open-­label, multicentre, phase III/IV, two-­ Protected by copyright. on two-­thirds of the interventional studies (hypotheses arm, parallel-­group RCTs, was undertaken to compare the generation), one for testing on the remaining third of efficacy and safety of insulin glargine versus comparator the interventional studies and one for testing on the treatments (including rosiglitazone, pioglitazone, insulin observational studies (hypotheses testing). Only the lispro, insulin lispro 75/25, neutral protamine Hagedorn hypotheses validated on at least one of the test data sets (NPH) insulin, NPH insulin 30/70 and lifestyle/dietary are carried through. According to the hypotheses gener- measures) in 2938 older (≥65 years) and younger adults ated, Q-­Finder extracts potential profiles of responders (<65 years) with T2DM. In this analysis, insulin glargine to Gla-300 from the database and examines the key was associated with better glycaemic control and a reduced characteristics of the patients who match these profiles incidence of daytime and any-­time-­of-­the-­day (24 hours) (figure 2). In order to reduce the risk of false-­positive hypoglycaemia compared with comparator interventions findings and to confirm the significance of the findings, in both younger and older T2DM patients.26 each patient profile will be adjusted for confounding So far, however, the pooled efficacy and safety of factors and a Bonferroni correction will be applied. Gla-300 have been examined only in preplanned meta-­ REALI project progress analyses of pivotal registration trials, and RWE related to From the end of 2017 to July 2019, eight European the effectiveness and safety of Gla-300 is mainly available studies were included in the REALI pooled raw database, for North America. Thus, the REALI programme expands of which three are interventional and five observational the analyses on the effectiveness and real-­world safety of (n=7121) (table 1). Three studies are currently being Gla-300 to include Europe, where healthcare delivery mapped to be added to the REALI data pool, leading to systems are different from those in North America, yet a total of 7584 patients included in the REALI database similar management guidelines are adopted. Further- by mid-2019. Further studies are still ongoing, which will more, the REALI project aims to identify and understand increase the number of patients with T1DM and T2DM the variation in patients’ experiences when treated with to more than 10 000 (table 1). At the end of the REALI Gla-300, and to gauge selected patient characteristics programme, 20 European countries will be represented that may be of interest to describe subsets of European in the data pool. populations with diabetes. To achieve these goals, the REALI programme uses two complementary statistical approaches, which enhance the chance of correctly iden- Discussion tifying subgroups of patients with specific effectiveness This collaborative European project aims to advance our and real-­world safety patterns. Highlighting the profiles understanding of the effectiveness and real-­world safety of patients who achieve greater glycaemic control will of Gla-300 predominantly in patients with T2DM, uncon- allow clinicians to provide personalised treatment plans trolled by their current glucose-­lowering regimen and in to patients with diabetes. 4 Freemantle N, et al. BMJ Open 2020;10:e033659. doi:10.1136/bmjopen-2019-033659 Open access BMJ Open: first published as 10.1136/bmjopen-2019-033659 on 28 April 2020. Downloaded from http://bmjopen.bmj.com/ on October 20, 2023 at Univesity Autonomous of Barcelona. Table 1 List of REALI studies Name of study Country(ies) Number Type** Duration Population Endpoint(s) Studies included in current database TOP-2 Germany/ 1865 Observational, 12 months T2DM: failure of a Effectiveness of Gla- Switzerland/ prospective, previous BOT with 300 BOT initiation Austria open-­label another basal insulin Toujeo-­Neo Germany 1693 Observational, 12 months T1DM and T2DM: Effectiveness of prospective, patients uncontrolled switching the basal product registry on BOT or BB regimen component of BOT or BB regimen to Gla- 300 Take Control* EU 771 Open-­label, 24 weeks T2DM: patient vs Efficacy and safety randomised physician-­managed 1:1, controlled, titration of Gla-300 parallel-­group Optin-­D The Netherlands 162 Observational, 6 months T2DM: treated with Changes over time in prospective, Gla-300 (BB) PROs (eg, emotional cohort well-­being, adherence, sleep quality and duration) Transition II France 193 Interventional, 24 weeks T2DM: uncontrolled Efficacy through single-­arm, on current basal improvement in HbA1c open-­label, insulin and eligible for and safety prospective a treatment change Protected by copyright. ITAS* Italy 458 Interventional, 24 weeks T2DM: physician-­ Efficacy and safety open-­label, managed vs patient-­ randomised, managed Gla-300 controlled, treatment in insulin-­ parallel-­group naïve patients Toujeo −1 Germany/ 1748 Observational, 12 months T2DM: initiated on Effectiveness of Gla- Switzerland prospective BOT 300 and success rate in achieving the predefined HbA1c treatment target Toujeo-­BB Hungary 231 Observational, 6 months T2DM: uncontrolled Effectiveness and prospective, on human BB insulin safety of Gla-300+ single-­arm regimen insulin glulisine, and glycaemic control improvement Studies pending MAGE Belgium 93 Observational, 6 months T2DM: treated with Change in DTSQ score prospective, BB in a real-­world single-­arm setting OPTIMIZE*** Belgium 58 Interventional, 28 weeks T1DM: uncontrolled Efficacy of optimising prospective, on twice daily basal treatment from twice single-­arm, insulin as part of BB daily basal to OD Gla- open-­label therapy 300 in combination with prandial rapid-­ acting insulin analogue in terms of improving HbA1c TOPAZ Czech Republic 312 Observational, 6 months T2DM: uncontrolled Effectiveness of Gla- prospective, on current basal 300 in improving single-­arm insulin in a real-­world glycaemic control, setting according to changes in HbA1c Continued Freemantle N, et al. BMJ Open 2020;10:e033659. doi:10.1136/bmjopen-2019-033659 5 Open access BMJ Open: first published as 10.1136/bmjopen-2019-033659 on 28 April 2020. Downloaded from http://bmjopen.bmj.com/ on October 20, 2023 at Univesity Autonomous of Barcelona. Table 1 Continued Name of study Country(ies) Number Type** Duration Population Endpoint(s) # Future studies to be added to the database T-­REG Poland 500 Prospective, 6 months Patients uncontrolled Effectiveness of product registry on NPH insulin or Gla-300 and HbA1c experiencing recurrent improvement of at nocturnal or severe least 0.5% hypoglycaemias GOAL-­Ro Romania 1100 Prospective, 6 months T2DM: insulin-­naïve Effectiveness of Gla- product registry patients in real-­world 300 on glycaemic practice control and hypoglycaemia ToGOAL Serbia 350 Prospective, 6–9 months T2DM: inadequately Effectiveness and product registry controlled on previous safety of Gla-300, basal or premixed including change in insulin HbA1c To upgrade Bulgaria 400 Prospective, 6 months T2DM: uncontrolled Effectiveness and product registry on NPH or premixed safety of Gla-300, insulin including change in HbA1c COBALTA Spain 106 Observational, 26 weeks T2DM: poorly Effectiveness and open-­label controlled on basal safety in terms of insulin and/or non-­ glycaemic control insulin antidiabetic (reduction of HbA1c) Protected by copyright. agents, receiving and reduction in basal insulin complications intensification with Gla-300 during hospitalisation or after discharge ***In the observational studies, all performed investigations and prescribed treatments are independent from patient participation in the study. †*In the randomised studies, randomisation is based on titration type (patient- vs physician-­managed) and not on treatment. ‡***A total of 72 Canadian patients enrolled in OPTIMIZE were excluded from the REALI database. §# The number of patients is an estimate based on the study protocol. BB, basal-­bolus; BOT, basal-­supported oral therapy; DTSQ, Diabetes Treatment Satisfaction Questionnaire; EU, European Union; Gla-300, insulin glargine 300 units/mL; HbA1c, haemoglobin A1c; NPH, neutral protamine Hagedorn; OD, once daily; PRO, patient-­reported outcome; T1DM, type 1 diabetes mellitus; T2DM, type 2 diabetes mellitus. Strengths and limitations key clinical and demographic characteristics at baseline, Considering that there may be differences in daily clin- as well as outcomes assessed at conventional time points, ical practice between Europe and other regions, one of was predefined for all studies, thereby limiting heteroge- the strengths of the REALI pooled analysis is the creation neity between the pooled studies. Moreover, the mixture of a large and prospective database from several multi- of study types, that is, observational and interventional, centre and/or multinational studies conducted across affords the opportunity to validate some assumptions in diverse diabetic populations in different European coun- one study type and to apply them in the other. tries. The use of such databases in diabetes research has Despite these strengths, several limitations of this several advantages. Aside from generating new hypoth- project must be acknowledged. First, even though the eses, a large database is representative of the target popu- REALI project is extracting information on predefined lation, and once set up, it is relatively quick and cheap minimum required variables common to all the studies to use compared with primary data collection.27 The included in the database, data collection may vary across REALI project is a unique database that provides the these studies, which can lead to inconsistency between opportunity to evaluate the effects of Gla-300, even in the results. Second, the combination of observational and patient subgroups with low representation in individual interventional data could increase the heterogeneity of studies, and to address alternative questions. Moreover, the findings and may introduce bias. However, this issue it allows us to confirm the effectiveness and tolera- will be addressed through stratified analyses of interven- bility of Gla-300 in real-­world clinical practice. Another tional and non-­ interventional studies. Third, bias(es) strength of the REALI project is that data collection of may exist in some data due to greater representation 6 Freemantle N, et al. BMJ Open 2020;10:e033659. doi:10.1136/bmjopen-2019-033659 Open access BMJ Open: first published as 10.1136/bmjopen-2019-033659 on 28 April 2020. Downloaded from http://bmjopen.bmj.com/ on October 20, 2023 at Univesity Autonomous of Barcelona. of some countries and/or between-­ study differences Merck, Sharp & Dohme, Bristol-­Myers Squibb, AstraZeneca and Janssen; Advisory in the management of patients, particularly regarding panel: Merck, Sharp & Dohme, Eli Lilly, Sanofi and Johnson & Johnson. PG: research: AstraZeneca, Novo Nordisk and Sanofi; speakers' bureau and consultancy: basal insulin titration. Finally, the REALI project shares Abbott, Amgen, AstraZeneca, Boehringer Ingelheim, Eli Lilly, Janssen, Merck Sharp the intrinsic methodological limitation of the observa- & Dohme, Novartis, Novo Nordisk, Sanofi, Servier and Takeda. DM: consultancy tional study design, with potential selection bias and the and/or speakers’ bureau: Almirall, Ascensia, AstraZeneca, Boehringer Ingelheim, increased likelihood of ‘missing’ or ‘not collected’ data GlaxoSmithKline, Eli Lilly, Ferrer, Janssen, Menarini, Merck, Sharp & Dohme, Novartis, Novo Nordisk and Sanofi. DMW: speakers’ bureau and consultancy/ compared with RCTs.28 Nevertheless, the size and diver- advisory panel: Amgen, AstraZeneca, Boehringer Ingelheim, MSD (Merck & Co.), sity of the patient populations of REALI, derived from Novartis, Novo Nordisk and Sanofi. GB: IVIDATA employee on behalf of Sanofi. CM: both interventional and observational studies and from IDDI employee. MR: Quinten employee. AC and MB: Sanofi employees. different therapy regimens, guarantee robust RWE closer Patient and public involvement Patients and/or the public were not involved in to daily clinical practice than classical RCTs.29 the design, or conduct, or reporting or dissemination plans of this research. Patient consent for publication Not required. ETHICS AND DISSEMINATION Provenance and peer review Not commissioned; externally peer reviewed. Ethical considerations The REALI project does not involve collection of primary Open access This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-­NC 4.0) license, which data. Moreover, all protocols were approved by the inde- permits others to distribute, remix, adapt, build upon this work non-­commercially, pendent local ethics committee/institutional review and license their derivative works on different terms, provided the original work is board at each study site or country, and all study partici- properly cited, appropriate credit is given, any changes made indicated, and the use pants provided written informed consent. Furthermore, is non-­commercial. See: http://​creativecommons.​org/​licenses/​by-​nc/​4.​0/. patient data is deidentified before inclusion in the REALI ORCID iD data pool. For these reasons, no ethical approval is Didac Mauricio http://​orcid.​org/​0000-​0002-​2868-​0250 required for the REALI project. Dissemination plan The authors will disseminate the findings of this project References 1 Tuomi T, Santoro N, Caprio S, et al. 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A consensus report by the 4 University Hospital Centre Toulouse Cardiovascular and Metabolic Medicine American diabetes association (ADA) and the European association Section, Toulouse, Midi-­Pyrénées, France for the study of diabetes (EASD). Diabetes Care 2018;41:2669–701. 5 INSERM, Paul Sabatier University, Toulouse, Occitanie, France 5 Sanchez-­Ibarra HE, Reyes-­Cortes LM, Jiang X-­L, et al. Genotypic 6 and phenotypic factors influencing drug response in Mexican Endocrinology & Nutrition, Hospital Universitari Germans Trias i Pujol, Barcelona, patients with type 2 diabetes mellitus. Front Pharmacol 2018;9:320. Spain 6 Twigg SM, Escalada J, Stella P, et al. Association of patient profile 7 Hospital de la Santa Creu i Sant Pau Institut de Recerca, Barcelona, Catalunya, with glycemic control and hypoglycemia with insulin glargine 300 Spain U/mL in type 2 diabetes: a post hoc patient-­level meta-­analysis. 8 Diabetes Ther 2018;9:2043–53. University Hospital Aachen, Aachen, Nordrhein-­Westfalen, Germany 9 IVIDATA, Paris, France 7 Cahn A, Raz I, Kleinman Y, et al. Clinical assessment of individualized 10 glycemic goals in patients with type 2 diabetes: formulation Global Diabetes, Sanofi SA, Paris, Île-­de-­France, France 11 of an algorithm based on a survey among leading worldwide IDDI SA, Louvain-­la-­Neuve, Belgium diabetologists. Diabetes Care 2015;38:2293–300. 12 Quinten, Paris, France 8 Blair HA, Keating GM. Insulin Glargine 300 U/mL: A Review in Diabetes Mellitus. Drugs 2016;76:363–74. Acknowledgements The authors would like to thank Niki Panagiotaki, PhD, and 9 Vargas-­Uricoechea H. Efficacy and Safety of Insulin Glargine 300 U/ mL versus 100 U/mL in Diabetes Mellitus: A Comprehensive Review Jane Juif, MSc, from HealthCare21 Communications Ltd (Macclesfield, UK), as well of the Literature. J Diabetes Res 2018;2018:1–28. as Thomas Rohban, MD, and Magalie El Hajj, MPharm, from Partner 4 Health (Paris, 10 White JR. Advances in insulin therapy: a review of new insulin France) for providing medical writing support. Conventional descriptive statistical glargine 300 Units/mL in the management of diabetes. Clin Diabetes analyses are being performed by IDDI (Louvain-­la-­Neuve, Belgium), while subgroup 2016;34:86–91. discovery analyses are being carried out by Quinten (Paris, France). 11 Matsuhisa M, Koyama M, Cheng X, et al. New insulin glargine 300 U/ ml versus Glargine 100 U/ml in Japanese adults with type 1 diabetes Contributors MB and AC led the protocol elaboration and organised data using basal and mealtime insulin: glucose control and hypoglycaemia collection and contributed to the statistical analyses plan. GB and CM contributed in a randomized controlled trial (edition JP 1). Diabetes Obes Metab to the conventional descriptive statistical analyses section and data pooling. MR 2016;18:375–83. contributed to the subgroup discovery design and its analysis plan. NF, RCB, PG, 12 Ritzel R, Roussel R, Bolli GB, et al. Patient-­Level meta-­analysis of the DM and DMW provided guidance on the design of data collection and pooling edition 1, 2 and 3 studies: glycaemic control and hypoglycaemia with and contributed to the statistical analyses plan. All authors provided input into new insulin glargine 300 U/ml versus Glargine 100 U/ml in people and reviewed and edited the manuscript, and approved the final version prior to with type 2 diabetes. Diabetes Obes Metab 2015;17:859–67. 13 Terauchi Y, Koyama M, Cheng X, et al. New insulin glargine 300 U/ml submission. versus Glargine 100 U/ml in Japanese people with type 2 diabetes Funding The REALI project is supported by Sanofi (Paris, France), including using basal insulin and oral antihyperglycaemic drugs: glucose performance of statistical analyses and medical writing. control and hypoglycaemia in a randomized controlled trial (edition JP 2). Diabetes Obes Metab 2016;18:366–74. Competing interests NF: research, travel or consultancy: Takeda, Pfizer, Biogen, 14 Bosnyak Z, Zhou FL, Jimenez J, et al. Predictive modeling of Tesaro, Allergan, Ipsen, Sanofi and AstraZeneca. RCB: speakers’ bureau: Sanofi, hypoglycemia risk with basal insulin use in type 2 diabetes: Freemantle N, et al. BMJ Open 2020;10:e033659. doi:10.1136/bmjopen-2019-033659 7 Open access BMJ Open: first published as 10.1136/bmjopen-2019-033659 on 28 April 2020. Downloaded from http://bmjopen.bmj.com/ on October 20, 2023 at Univesity Autonomous of Barcelona. use of machine learning in the lightning study. Diabetes Ther signposts for clinicians? [Poster]. Available: https://​easddistribute.​ 2019;10:605–15. m-​anage.​com/​from.​storage?​image=​4iBH​9mRQ​m1kf​eEHU​LC2C​ 15 Sullivan SD, Bailey TS, Roussel R, et al. 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