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Phenotype Submission - Drug Resistant Epilepsy

We have decided to submit the drug resistant epilepsy phenotype that was recently published in Epilepsia and presented at the OHDSI symposium for review by the phenotype library. @Gowtham_Rao @cukarthik

Clinical Description (From OHDSI Symposium 2022 Poster #86):
Patients meet the consensus criteria for drug-resistant epilepsy (DRE) when they fail two or more appropriate medication regimens. However, this definition is not readily translated to common observational data sources. We developed EHR based computable phenotypes using the OMOP CDM to accurately and reliably identify patients with DRE at Columbia University Irving Medical Center (CUIMC).

From the Epilepsia manuscript by Castano et. al.:
“Approximately one third of patients with epilepsy continue to have seizures despite two or more appropriate medication regimens and meet the consensus definition for drug-resistant epilepsy (DRE).” (Kwan P Epilepsia, Kwan P NEJM)

"The International League Against Epilepsy (ILAE) has defined DRE by consensus as “failure of adequate trials of two tolerated, appropriately chosen and used antiepileptic drug schedules to achieve sustained seizure freedom.” (Kwan P et. al. Epilepsia)

“With continued polypharmacy alone, the chances of achieving seizure freedom are modest, perhaps as low as 3%.”

“Patients with uncontrolled seizures are at increased risk of death, injury, cognitive decline, psychiatric illness, and decreased quality of life.”

“DRE is also associated with substantially higher relative costs of illness.”

Literature Review:
A literature review was done in preparation for the recent publication (Identification of patients with drug-resistant epilepsy in electronic medical record data using the Observational Medical Outcomes Partnership Common Data Model - PubMed). Some representative references are below

Kwan P, Brodie MJ. Early identification of refractory epilepsy. N Engl J Med . 2000; 342(5): 314– 9.

Kwan P, Arzimanoglou A, Berg AT, Brodie MJ, Allen Hauser W, et al. Definition of drug resistant epilepsy: consensus proposal by the ad hoc task force of the ILAE commission on therapeutic strategies. Epilepsia . 2010; 51(6): 1069– 77.

Brodie MJ, Barry SJE, Bamagous GA, Norrie JD, Kwan P. Patterns of treatment response in newly diagnosed epilepsy. Neurology . 2012; 78(20): 1548– 54.

Sperling MR, Barshow S, Nei M, Asadi-Pooya AA. A reappraisal of mortality after epilepsy surgery. Neurology . 2016; 86(21): 1938– 44.

Jokeit H, Ebner A. Long term effects of refractory temporal lobe epilepsy on cognitive abilities: a cross sectional study. J Neurol Neurosurg Psychiatry . 1999; 67(1): 44– 50.

Spencer SS, Berg AT, Vickrey BG, Sperling MR, Bazil CW, Haut S, et al. Health-related quality of life over time since resective epilepsy surgery. Ann Neurol . 2007; 62(4): 327– 34.

Begley C, Wagner RG, Abraham A, Beghi E, Newton C, Kwon CS, et al. The global cost of epilepsy: a systematic review and extrapolation. Epilepsia . 2022; 63(4): 892– 903.

Willems LM, Hochbaum M, Frey K, Schulz J, Menzler K, Langenbruch L, et al. Multicenter, cross-sectional study of the costs of illness and cost-driving factors in adult patients with epilepsy. Epilepsia . 2022; 63(4): 904– 18.

We have tabulated the results from prior studies that have validated drug resistant epilepsy with source-level data in our publication. Here are those references:

Freedman DA, Grinspan Z, Glynn P, Mittlesteadt J, Dawes A, Patel AD. Validating coding for the identification of pediatric treatment resistant epilepsy patients. Child Neurol Open. 2021;8:2329048X211037806.

Pan S, Wu A, Weiner M, Grinspan MZ. Development and evaluation of computable phenotypes in pediatric epilepsy: 3 cases. J Child Neurol. 2021;36(11):990-7.

Hill CE, Lin CC, Terman SW, Rath S, Parent JM, Skolarus LE, et al. Definitions of drug-resistant epilepsy for administrative claims data research. Neurology. 2021;97(13):e1343-50

Logic Description:
Our index event was any visit between 01/01/2015 and 04/01/2020. Additionally, patients had to have at least 1 intractable epilepsy diagnosis between all and 0 days prior to the visit and at least 2 distinct 90-day drug eras of non-gabapentinoid antiseizure medications anytime between all and 90 days prior to the index visit. We also restricted to patients who had at least 365 days of observation after the index event.

We calculated the sensitivity, specificity, PPV, NPV and F1 score of this phenotype by cross validation with a random sample of 600 epilepsy patients from a previously validated cohort. We compared the performance of this phenotype to multiple alternatives.

Among 412 patients with source record-confirmed epilepsy, 62 (15.0%) had DRE, 163 (39.6%) had drug-responsive epilepsy, 124 (30.0%) had undefined drug responsiveness, and 63 (15.3%) had insufficient records. The best performing phenotype for DRE in terms of the F1 score was the presence of ≥1 intractable epilepsy code and ≥2 unique non-gabapentinoid ASM exposures each with ≥90-day drug era (sensitivity = .661, specificity = .937, PPV = .594, NPV = .952, F1 score = .626). Several phenotypes achieved higher sensitivity at the expense of specificity and vice versa.

Overall, the F1 score was highest for this phenotype. A more extended explanation of the validation process can be found in the poster or publication.

Drug Resistant Epilepsy Phenotype.docx (67.2 KB)

Hi @mattspotnitz - thank you for this submission.

To mark your submission as complete and to assign a peer reviewer - could you please add the following content. You may edit the post above - to ensure it meets these requirements. Requirements are detailed here Cohort Definition Submission Requirements • PhenotypeLibrary

  1. Clinical description -
  1. Literature review - was there any literature that you found that validated drug resistant epilepsy definitions on observational data?

  2. Cohort definition submitted as a cohort definition set R object - in future we will require the definitions to be submitted as a R cohort definitions et object. A draft guidance on it is here Guidelines on Cohort Definition Set R Object • PhenotypeLibrary. For now, if you can attach .txt file with the cohort json that would meet the requirement. Could you please attache the json as a .txt file. Please also give a name for the cohort definition - please keep the number of characters to <90 valid characters as described here Validity checks for Cohort Definitions • PhenotypeLibrary I will build the cohort definition set object. Please make sure there is no name clash with cohort definitions here https://atlas-phenotype.ohdsi.org/ you may submit more than one cohort definition.

  3. Cohort Diagnostics output - we require cohort diagnostics (version 3+ recommended) to be executed on 1 or more data sources. PheValuator is optional. If need assistance to post it on data.ohdsi.org , you can send me the output of CD directly and i will post it.

  4. Discuss your evaluation/validation findings - Would it be possible to copy the content to this forum post (and attach the poster). I know it is additional work, i am sorry about that. But the reason i am asking is to make these posts ‘encapsulate’ as much information as possible - so that the peer reviewer does not have to go searching for content.

Thanks for updating the post!

The main pending item is Cohort diagnostics run on at least one data source. Would you like assistance with that? If yes, I can create a script or a package for you to execute.

Hi @Gowtham_Rao,

Yes, it would be great if you could help us with cohort diagnostics. Thanks a lot!

hi @mattspotnitz

could you please share the cohort json as a .txt (notepad) file instead of .docx file. The reason - word being a rich text editor malforms some of the content in the cohort specification.

Hi @Gowtham_Rao,
Unfortunately, this website does not allow me to upload .txt files. Is there another way I can get the JSON to you?

Ooh really? I did not know that. Can you please email it to me

@mattspotnitz thank you for sending the cohort definition expression json as a .txt file. We have to figure out how we can share the jsons more easily. Maybe @admin could comment on this. Would it be possible to add .json or .txt as an authorized file structure.

@mattspotnitz some feedback - all technical review and not scientific review (for now)

  1. Unused concept sets in cohort definitions. Could those be removed?

  2. Use of non standard concepts - this is, unless explained, not acceptable to the OHDSI phenotype library. is there a reason why non standard codes were used?

  3. Indexing on any visit - this is a minor comment, as continuous drug era rule may justify this. But in general, the phenotype library will flag cohort definitions that have ‘any visit’ or ‘any condition’ as entry criteria. If there is a way to specify a concept set there - it would be nicer

@mattspotnitz another question to ask, and potentially use in your cohort definition is - do people, once considered to have drug resistant epilepsy ever stop being considered to have drug resistant epilepsy? The answer is probably no - but if it is yes, then you may want to consider ways to model cohort end date

@Gowtham_Rao @mattspotnitz ‘.txt’ files are now allowed as file uploads in the OHDSI forums.

1 Like

Attaching the submitted cohort json
DRE.txt (183.3 KB)

I was looking at the cohort definition today

I removed the unused conceptSets (Best practice)

in the conceptSet named Intractable Epilepsy 2021-02-21,

it leaves many non standard concepts

and the cohort definition does not use non standard codes (its not referencing condition_source_concept_id)

could you please remediate and resubmit.

Hi @Gowtham_Rao, we are submitting a logically equivalent and validated drug-resistant phenotype that does not index on visit. Also, the redundant concept sets have been removed. However, the non-standardized codes will remain in the concept set.
DREPhenLib.txt (39.3 KB)

This version looks so much better @mattspotnitz - this passes technical review.
I have put your cohort in the Phenotype library atlas instance here ATLAS
The cohort Id is 254 (and will persist as constant in OHDSI Phenotype Library) and becomes referenceable.

However - this is not considered ACCEPTED. To be accepted, it has to be independently peer reviewed and recommended for acceptance. Before initiating peer review, i will ask that you run Cohort Diagnostics on this on your data source and submit results to OHDSI.

The package is here https://github.com/gowthamrao/PhenotypeDrugResistantEpilepsy

Please run the package and submit the results. Once we get the results - i will find someone to do peer review.