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  string(91) "Individual Participant-Level Data, which includes Full CSR and all supporting documentation"
  ["property_scientific_abstract"]=>
  string(1567) "Background: Volume depletion as adverse events (AE) by sodium-glucose cotransporter-2 inhibitors (SGLT2i) due to its diuretic effect, may raise the concern about the risk of lacunar stroke; however, earlier RCTs or meta-analysis reported no significant increase in the incidence of stroke without clearly distinguishing stroke subtypes. Based on the pharmacovigilance study using a real-world database from Japan, we had previously proposed the hypothesis that SGLT2i may affect the risk of stroke differently depending on the subtype of stroke, in a way to increase the risk of ischemic stroke but to decrease the risk of hemorrhagic stroke.

Objective: We aim to validate the above hypothesis.

Study Design: Retrospective analysis of association between the incidence of stroke (subtypes) and the use of SGLT2i.

Participants: Participants from 6 clinical trials receiving canagliflozin compared to matched control.

Main Outcome Measure: Incidence of stroke (subtypes) following the use of SGLT2i.

Statistical Analysis: Subtype-wise stroke adverse events (e.g., ischemic and hemorrhagic stroke) were separately summarized to calculate odds ratio for the incidence of each stroke subtype during the follow-up period (binary). Then we use multi-level logistic regression. In addition, if we could use the period from medication start to the development of stroke, we will use Cox-proportional hazard test (including each trial as frailty term) to compare the hazard to develop each stroke subtype between the treatment arm and control arm."
  ["project_brief_bg"]=>
  string(3092) "Sodium-glucose cotransporter-2 inhibitors (SGLT2i) are the newest class of peroral hypoglycemic agents that are commercially available for type 2 diabetes mellitus (DM) treatment. It has a weak loop diuretic effect [1-3] leading to lowered body weight and blood pressure, and SGLT2i reduces major cardiovascular adverse events (AEs) and also reduces the risk of renal disease progression [4,5]. The diuretic effect can result in volume depletion [6-8], orthostatic hypotension [9], and dehydration [3], which may raise concern about the increased risk of ischemic stroke [3]. Whereas a few of earlier studies reported a tendency for the increased risk of non-fatal stroke development following SGLT2i use [10], in many earlier meta-analysis studies the risk of non-fatal stroke following SGLT2i use was reported not to have increased nor decreased [5,11,12].

One potential bias in the non-significant effect for the risk of stroke following SGLT2i use is that earlier randomized controlled trials (RCTs) investigating the safety of SGLT2i used the aggregated incidence of non-fatal stroke of any subtype for statistical analysis without distinguishing different stroke subtype (e.g. ischemic and hemorrhagic) [13-15]. However, risk factors for developing stroke vary in each stroke subtype [16-18].

The diuretic effect of SGLT2i may decrease the risk of embolism and hemorrhagic stroke by ameliorating hypertension and congestive heart failure causing atrial fibrillation [19, 20], while it may increase the risk of lacunar infarction by the elevated hematocrit and excessive dehydration [21]. We suspected that such discrepancy in the effect of SGLT2i on the risk of each stroke subtype may have masked the overall incidence of stroke, resulting in the non-significant stroke risk concluded by the previous studies.

To address this point, in our previous study we have conducted a disproportionate analysis as the pharmacovigilance approach, using a large Japanese AE self-reporting database [22]. As a result, the SGLT2i showed varying degree of significantly higher reporting  for all ischemic stroke, thrombosis, lacunar infarction, and embolism, but no significant higher reporting for hemorrhagic stroke. These results provides us the hypothesis that the development of stroke following SGLT2i use may possibly differ depending on the stroke subtypes.

However, since the self-reporting database contains many limitations that are inherent in this type of database, such as reporting bias, insufficient clinical covariates available, and the lack of denominators [9, 23], analyzing observational data is essential to validate this hypothesis.

We consider that using the data from YODA database will be rationalized because the dehydration due to the use of diuretics can also be seen within the short-term period after its administration, and also because the results obtained from this study will be the basis for the future risk-stratified research, even though the included studies are the short-term studies on patients with lower cerebrovascular risks."
  ["project_specific_aims"]=>
  string(560) "To evaluate the degree of risk developing stroke subtypes following the use of canagliflozin.

We aim to validate our hypothesis that SGLT2i may affect the risk of stroke differently depending on its subtype: increasing the risk of ischemic stroke but decreasing the risk of hemorrhagic stroke. In this project, we aim to validate our hypothesis. And such discrepancy in the effect of SGLT2i on the risk of each stroke subtype may have masked the overall incidence of stroke, resulting in the non-significant stroke risk concluded by the previous studies."
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  ["project_purposes"]=>
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    [0]=>
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      ["value"]=>
      string(49) "New research question to examine treatment safety"
      ["label"]=>
      string(49) "New research question to examine treatment safety"
    }
    [1]=>
    array(2) {
      ["value"]=>
      string(69) "Confirm or validate previously conducted research on treatment safety"
      ["label"]=>
      string(69) "Confirm or validate previously conducted research on treatment safety"
    }
    [2]=>
    array(2) {
      ["value"]=>
      string(66) "Summary-level data meta-analysis using only data from YODA Project"
      ["label"]=>
      string(66) "Summary-level data meta-analysis using only data from YODA Project"
    }
  }
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    ["value"]=>
    string(7) "RStudio"
    ["label"]=>
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  ["project_research_methods"]=>
  string(734) "Retrospective analysis of subtype-wise stroke risk in patients treated with canagliflozin, by evaluating patient-level data from 6 clinical studies as follows: NCT01809327, NCT01381900, NCT01340664, NCT02025907, NCT00650806, and NCT02243202. 

Inclusion criteria:

1.	Participants treated with canagliflozin or control, with either sex, any age, ethnicity, and HbA1c.

Exclusion criteria:

1.	No sufficient information on the above variables and some additional covariates as follows: history of smoking, dyslipidemia, hypertension, use of antithrombosis or anticoagulants, use of other types of anti-diabetic drug, use of diuretics, history of cardiovascular diseases, and the history of cerebrovascular diseases."
  ["project_main_outcome_measure"]=>
  string(201) "The primary outcome measure is the adjusted odds ratio of stroke (subtypes) following the use of SGLT2i during the certain period of follow-up. Stroke is defined as the AE newly diagnosed and reported."
  ["project_main_predictor_indep"]=>
  string(136) "The exposure to SGLT2i (here canagliflozin) as treatment arm.

We also include sex, age, ethnicity, and BMI as mandatory variables."
  ["project_other_variables_interest"]=>
  string(453) "In addition, we include the following variables into models if they are available in most of the trials: history of smoking, dyslipidemia, hypertension, use of antithrombosis or anticoagulants, use of other types of anti-diabetic drug, use of diuretics, history of cardiovascular diseases, history of cerebrovascular diseases, amount of urine, and laboratory findings at baseline (serum creatinine, HbA1c, blood hematocrit, hemoglobin, plasma BNP, etc)."
  ["project_stat_analysis_plan"]=>
  string(766) "We will first summarize subtype-wise stroke adverse events (e.g., ischemic and hemorrhagic stroke) separately in order to calculate unadjusted odds ratio for the incidence of each stroke subtype during the certain follow-up period (developed or not: binary), in each trial included. Then adjusted odds ratio will be calculated as a fixed effect in multi-level logistic regression analysis, where each trial is incorporated as random effect.

In addition, if we could use the period from medication start to the development of stroke, we will use Cox-proportional hazard test (including each trial as frailty term) to compare the hazard to develop each stroke subtype between the treatment arm and control arm.

All analysis will be conducted using R 3.5.1."
  ["project_timeline"]=>
  string(271) "Application submission: May 2020

Project start date: June 2020

Analysis completion: Early 2021

Date results reported back to the YODA project (before submission): Early 2021

First manuscript submission: Early 2021

Project end date: June 2021"
  ["project_dissemination_plan"]=>
  string(149) "We are planning to submit the manuscript to journals of which scope is in diabetics or in neurology (such as "Journal of the Neurological Sciences")."
  ["project_bibliography"]=>
  string(4398) "
[1] Kimura G. Importance of inhibiting sodium-glucose cotransporter and its compelling indication in type 2 diabetes: pathophysiological hypothesis. J Am Soc Hypertens. 2016 Mar;10(3):271-8.

[2] Hsia DS, Grove O, Cefalu WT. An update on sodium-glucose co-transporter-2 inhibitors for the treatment of diabetes mellitus. Curr Opin Endocrinol Diabetes Obes. 2017 Feb;24(1):73-79.

[3] Kimura G. Sodium-Glucose Cotransporter 2 (SGLT2) Inhibitors and Stroke. Circ J. 2017 May 25;81(6):898.

[4] Fitchett D, Zinman B, Wanner C, et al. Heart failure outcomes with empagliflozin in patients with type 2 diabetes at high cardiovascular risk: results of the EMPA-REG OUTCOME trial. Eur Heart J. 2016 May 14;37(19):1526-34.

[5] Zelniker TA, Wiviott SD, Raz I, et al. SGLT2 inhibitors for primary and secondary prevention of cardiovascular and renal outcomes in type 2 diabetes: a systematic review and meta-analysis of cardiovascular outcome trials. Lancet. 2019 Jan 5;393(10166):31-39.

[6] Raschi E, Parisotto M, Forcesi E, et al. Adverse events with sodium-glucose co-transporter-2 inhibitors: A global analysis of international spontaneous reporting systems. Nutr Metab Cardiovasc Dis. 2017 Dec;27(12):1098-1107.

[7] Ueda P, Svanstrm H, Melbye M, et al. Sodium glucose cotransporter 2 inhibitors and risk of serious adverse events: nationwide register based cohort study. BMJ. 2018 Nov 14;363:k4365.

[8] Lupsa BC, Inzucchi SE. Use of SGLT2 inhibitors in type 2 diabetes: weighing the risks and benefits. Diabetologia. 2018 Oct;61(10):2118-2125.

[9] Fadini GP, Bonora BM, Avogaro A. SGLT2 inhibitors and diabetic ketoacidosis: data from the FDA Adverse Event Reporting System. Diabetologia. 2017 Aug;60(8):1385-1389.

[10] Wu JH, Foote C, Blomster J, et al. Effects of sodium-glucose cotransporter-2 inhibitors on cardiovascular events, death, and major safety outcomes in adults with type 2 diabetes: a systematic review and meta-analysis. Lancet Diabetes Endocrinol. 2016 May;4(5):411-9.

[11] Sonesson C, Johansson PA, Johnsson E, et al. Cardiovascular effects of dapagliflozin in patients with type 2 diabetes and different risk categories: a meta-analysis. Cardiovasc Diabetol. 2016 Feb 19;15:37.

[12] Guo M, Ding J, Li J, et al. SGLT2 inhibitors and risk of stroke in patients with type 2 diabetes: A systematic review and meta-analysis. Diabetes Obes Metab. 2018 Aug;20(8):1977-1982.

[13] Neal B, Perkovic V, Mahaffey KW, et al. Canagliflozin and Cardiovascular and Renal Events in Type 2 Diabetes. N Engl J Med. 2017 Aug 17;377(7):644-657.

[14] Zinman B, Wanner C, Lachin JM, et al. Empagliflozin, Cardiovascular Outcomes, and Mortality in Type 2 Diabetes. N Engl J Med. 2015 Nov 26;373(22):2117-28.

[15] Wiviott SD, Raz I, Bonaca MP, et al. Dapagliflozin and Cardiovascular Outcomes in Type 2 Diabetes. N Engl J Med. 2019 Jan 24;380(4):347-357.

[16] Adams HP Jr, Bendixen BH, Kappelle LJ, et al. Classification of subtype of acute ischemic stroke. Definitions for use in a multicenter clinical trial. TOAST. Trial of Org 10172 in Acute Stroke Treatment. Stroke. 1993 Jan;24(1):35-41.

[17] Amarenco P, Bogousslavsky J, Caplan LR, et al. Classification of stroke subtypes. Cerebrovasc Dis. 2009;27(5):493-501.

[18] Bladin CF, Chambers BR. Frequency and pathogenesis of hemodynamic stroke. Stroke. 1994 Nov;25(11):2179-82.

[19] Boehme AK, Esenwa C, Elkind MS. Stroke Risk Factors, Genetics, and Prevention. Circ Res. 2017 Feb 3;120(3):472-495.

[20] Gage BF, Waterman AD, Shannon W, et al. Validation of clinical classification schemes for predicting stroke: results from the National Registry of Atrial Fibrillation. JAMA. 2001 Jun 13;285(22):2864-70.

[21] Song SH, Kim JH, Lee JH, et al. Elevated blood viscosity is associated with cerebral small vessel disease in patients with acute ischemic stroke. BMC Neurol. 2017 Jan 31;17(1):20.

[22] Sato K, Mano T, Iwata A, Toda T. Subtype-Dependent Reporting of Stroke With SGLT2 Inhibitors: Implications From a Japanese Pharmacovigilance Study. J Clin Pharmacol. 2019 Dec 2. doi: 10.1002/jcph.1561. [Epub ahead of print]

[23] Michel C, Scosyrev E, Petrin M, et al. Can Disproportionality Analysis of Post-marketing Case Reports be Used for Comparison of Drug Safety Profiles? Clin Drug Investig. 2017 May;37(5):415-422.
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