Patient Perspectives on Antiseizure Medication Discontinuation: A Mixed-Methods Exploration of Risk Perception, Tolerance, and Counseling.

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Learn more: PMC Disclaimer | PMC Copyright Notice Neurol Clin Pract . 2025 May 2;15(3):e200475. doi: 10.1212/CPJ.0000000000200475 Patient Perspectives on Antiseizure Medication Discontinuation A Mixed-Methods Exploration of Risk Perception, Tolerance, and Counseling Samuel W Terman 1, ✉ , Jordan M Silva 2 , Max Kuster 3 , Jasper Lee 4 , Amanda P Brand 4 , Kara Manuel 2 , Navya Kalia 2 , Micaela Dugan 2 , Marla Reid 3 , Katherine Mortati 3 , Alexandra Tolmasov 3 , Palak S Patel 5 , James F Burke 6 , Arthur C Grant 7 , Chloe E Hill 1 , Susanna S O'Kula 3 Author information Article notes Copyright and License information 1 Department of Neurology, University of Michigan, Ann Arbor; 2 University of Michigan Medical School, Ann Arbor; 3 State University of New York Downstate Health Sciences, Department of Neurology, Brooklyn; 4 Hackensack Meridian School of Medicine, Nutley, NJ; 5 John F. Kennedy University Medical Center Departments of Neurology and Psychiatry, Edison, NJ; 6 Department of Neurology, the Ohio State University, Columbus; and 7 Department of Neurology, State University of New York Downstate Health Sciences, University, Brooklyn. ✉ Correspondence Dr. Terman sterman@umich.edu Submitted and externally peer-reviewed. The handling editor was Editor Luca Bartolini, MD, FAAN, FAES. ✉ Corresponding author. Received 2024 Nov 5; Accepted 2025 Mar 5; Issue date 2025 Jun. © 2025 American Academy of Neurology PMC Copyright notice PMCID: PMC12054744  PMID: 40336929 See the article " To Take or Not to Take Antiseizure Medications ", e200482. Abstract Background and Objectives Antiseizure medications (ASMs) are standard treatment for epilepsy. Yet, because ASMs can have adverse effects, guidelines suggest considering ASM withdrawal after a period of seizure freedom. We explored patients' perceived seizure risk, seizure risk tolerance, and risk counseling techniques. Methods We interviewed adults at least one-year seizure free, seen for epilepsy across 3 academic institutions. Participants rated their own perceived seizure risks (0 “definitely would not have another seizure” to 10 “definitely would”) on vs off ASMs, discussed what minimal clinically important differences would be to justify ASM continuation, rated how likely they might be to withdraw ASMs (1 “not at all likely” to 7 “extremely likely”) under different hypothetical seizure risks, and recalled their previous seizure risk counseling. Results The median age (N = 32) was 46 years (interquartile range [IQR] 33–56), with a median of 3 years since their last seizure (IQR 2–11). Participants rated their two-year chance of another seizure on ASMs as a median 1 (IQR 0 to 2) on a “0–10” scale, compared with a median 5 (IQR 4 to 7) off ASMs. Participants believed that their current ASMs have a median effectiveness of 9 (IQR 7–10) on a “0–10” scale. Participants believed that a median effectiveness of 6 (IQR 4 to 9) on a “0–10” scale would warrant remaining on ASMs, although 5 participants would continue their ASM if it extended the time until next seizure by any amount no matter how small. Regarding how likely they would be to withdraw ASMs under different hypothetical seizure risks, median responses on a “1–7” scale were 5 (IQR 1–6) when shown two-year seizure risks of 10% on vs 11% off ASMs, 1 (1–3) if 10% vs 20%, and 1 (1–2) if 25% vs 50%. No participant recalled having been presented with numerical seizure estimates regarding possible ASM withdrawal, yet 16 (50%) would like this information particularly in our presented graphical format. Discussion Participants believed that their ASMs were highly effective and were often reluctant to withdraw. Showing hypothetical seizure risks influenced decisions, and graphical risk communication tools were generally welcomed. Introduction Antiseizure medications (ASMs) represent the mainstay of epilepsy treatment. Seizure elimination represents an important goal, given that seizures may lead to injuries, status epilepticus, and driving and work restrictions and worsen quality of life. 1 - 3 ASMs may reduce the risk of a seizure recurrence by approximately 50%. 4 However, adverse effects range from 10% to 40% in unstructured screening or up to 60%–90% 5 in structured screenings and correlate with worse quality of life. 1 , 6 - 9 Two-thirds of patients with epilepsy experience prolonged seizure freedom while on ASMs, 10 and 50%–70% will remain seizure free once tapered off. 11 , 12 Guidelines have suggested to complete an individualized risk assessment after 2 years of seizure freedom 13 and discuss the risks and benefits of ASM discontinuation. 14 Decisions depend on accurately estimating a patient's postdiscontinuation risk and understanding how patients feel about their ASMs and their risk of recurrent seizures. However, scarce literature has explored patient risk perception or risk tolerance in this context. 15 One qualitative study probed patient attitudes after discontinuation but did not investigate how patients would interpret different seizure risk thresholds. 16 Improved understanding of what patients might find to be acceptable risk thresholds or minimal clinically important differences would help align expert consensus with patient values and inform future guidelines. 17 We conducted a mixed-methods interviewer-assisted survey to understand patient perceptions of risk and acceptable seizure risk thresholds when considering ASM discontinuation in the context of prolonged seizure freedom. Methods Participants and Recruitment We screened serial medical records of patients at least 18 years old with a clinic visit for a primary diagnosis of epilepsy within the past month, at 3 centers: John F. Kennedy University Medical Center (JFK), State University of New York (SUNY) Downstate Health Sciences University, and University of Michigan (UM). Throughout this article, direct quotations from participants are labeled according to their institution, for example J# refers to participants from JFK, S# from SUNY, and M# from UM. While past guidelines have suggested considering ASM discontinuation after 2 years of seizure freedom, 14 , 18 we defined eligibility for our study as at least one-year seizure free. Such patients have a high chance of remaining seizure free, more updated guidelines no longer recommend any two-year cutoff, 13 and restricting further would have reduced sample size and increased selection bias. We contacted eligible participants using 2 initial telephone attempts and then email if no response. 19 - 21 Our sample size was determined on achieving thematic saturation when no new dominant themes were uncovered by additional interviews, after obtaining representation across key informant demographics (age, race, seizure semiology, years seizure free). 22 - 26 Questionnaire Development and Content We assembled multidisciplinary experts in epileptology, risk communication, and implementation science to design our questionnaire. The interview was delivered over Zoom at UM and JFK but mostly in-person at SUNY as feasible for each site. The interviewee answered questions displayed on PowerPoint slides and explained their answers (eAppendix 1; Figure 1 ). Figure 1. Example Interview Questions. Open in a new tab These are excerpted from the Appendices, which show our full instruments. Top left: We asked participants questions on a 0–10 scale regarding what they think the chance of another seizure would be on vs off ASMs and also how effective they think their current ASMs are and how effective an ASM would need to be for them to wish to keep taking it. This shows 1 such example of these “0–10” scale questions. Top right: We asked patients to choose one of these 4 options and explain their choice and what they might consider “too much” or “a lot.” Bottom left: This is an example pictograph in which we presented participants with hypothetical seizure risks on vs off ASMs and asked participants how likely they would be to withdraw ASMs if those risks applied to them. There were a total of 3 such pictographs. Bottom right: After viewing all pictographs, we asked participants how helpful they might find seeing such numbers in this way for risk counseling. First, we explored perceptions about seizure risk susceptibility. We asked, “What do you think your chance of another seizure might be in the next two years” on vs off ASMs, with choices displayed on a number line ranging between 0 (definitely would not have another seizure) and 10 (definitely would have another seizure). We then asked participants how effective they feel their ASM has been, on a scale from 0 (doing nothing to prevent seizures) to 10 (guaranteeing no more seizures). Second, we explored minimal clinically important differences. We presented another number line, asking “I would keep taking an ASM…” with choices ranging between 0 (even if it did nothing to prevent seizures) and 10 (only if it guaranteed no more seizures). We then asked open-ended questions regarding what respondents might consider to be a meaningful effect. Participants were then asked what other metrics might persuade them to remain on ASMs (e.g., improvements in the number, severity, or time delay until seizures). Third, we asked how likely participants might be to consider discontinuation (from 1 [extremely unlikely] to 7 [extremely likely]) under 3 hypothetical scenarios. Each scenario presented 2 numbers: a hypothetical seizure risk on vs off ASMs. Numbers were displayed through pictographs ( Figure 1 ). 27 , 28 Pictographs displayed 100 participant icons, some of which were colored to convey a percentage. This provided a clear numerator and denominator and presented information visually for increased comprehension. We started with a 10% vs 20% (“medium-risk”) scenario and a 25% vs 50% (“high-risk”) scenario, informed by existing literature. 4 , 29 - 31 Given initial conservative responses to the medium-risk scenario, we added a 10% vs 11% (“low-risk”) scenario to explore floor effects. Fourth, respondents discussed what risk counseling information they recall having received. Additional Variables We abstracted data from electronic medical records: age, sex, race, seizure characteristics, years since most recent seizure, past and current ASMs, epilepsy etiology, and EEG findings. After the interview, all participants were asked to fill out a brief postinterview survey (eAppendix 2) reporting their general beliefs about medication harms, 32 , 33 desired intensity of medical care, 34 self-reported numeracy, 35 and potential interest in weaning ASMs if their doctor felt that it was indicated. This was part of a larger mixed-methods study, but we report only those responses that are within this article's scope here. Analysis Quantitative results were described using interquartile ranges (IQRs), histograms, and scatterplots for continuous data and percentages for dichotomous data. To evaluate for nonresponse bias, we compared characteristics (eTable 1) per medical records of eligible participants who did vs did not participate using Fisher exact tests or χ 2 tests for dichotomous variables, or Student t tests or Wilcoxon rank-sum tests for continuous variables. Data were analyzed using Stata 17.0 (College Station, TX). Interviews were transcribed verbatim and entered into Dedoose 9.2.5 (Los Angeles, CA: SocioCultural Research Consultants, LLC). Two coders reviewed each transcript using both deductive (researcher-driven) and inductive (response-based) reasoning. Differences in coding schemes were resolved by consensus. Standard Protocol Approvals, Registrations, and Participant Consents This study was approved by each site's institutional review board (UM: HUM00209220; SUNY Downstate: 2018295; JFK: Pro2023-0092). Data Availability Data can be shared on request and in compliance with required data use agreements. Results Population Description We screened 189 adults with epilepsy, of whom 74 (40%) were seizure free for at least one year and thus contacted. Thirty-two (43% of 74) participated. Age ranged from 19 to 84 years (median 46, IQR 33–56). Seizure-free duration ranged from 1 to 35 years (median 3, IQR 2–11). Additional characteristics are provided in Table 1 . eTable 1 (postinterview survey) suggests that this population endorsed high numeracy and favorable beliefs toward medications in general. Table 1. Population Description (N = 32) Variable Values No. (%) or median (interquartile range); range Site SUNY 15 (47) UM 11 (34) JFK 6 (19) Age 46 (33–56); range 19–84 Female 15 (47) Race White 16 (50) Black 14 (44) Asian 2 (6) Other 0 (0) Ethnicity Hispanic/Latino 2 (6) Surrogate responder 3 (9) Age at first seizure 21 (13–29); range 0–73 Years between first and most recent seizure 12 (4–23); range 0–65 Years since most recent seizure 3 (2–11); range 1–35 Seizures impaired awareness 31 (97) Motor seizures 30 (94) Focal-onset seizures No 3 (9) Yes 26 (81) Unknown 3 (9) Brain surgery Refractory epilepsy surgery 7 (22) Any other 4 (13) 1st or 2nd-degree relative with epilepsy No 22 (69) Yes 7 (22) Unknown 3 (9) History of febrile seizures No 29 (91) Unknown 3 (9) At least 10 seizures, lifetime 19 (59) Self-limited epilepsy syndrome 0 (0) History of convulsive status epilepticus 4 (13) Developmental delay 3 (9) Abnormal neurologic examination Any 8 (25) Cognitive/language 4 (13) Motor 4 (13) Sensory 3 (9) Epilepsy etiology Unknown 18 (56) Structural* 10 (31) Genetic 3 (9) Infectious 2 (6) Most recent EEG, epileptiform findings No previous EEG 7 (22) Epileptiform 8 (25) Not epileptiform 17 (53) Number of current ASMs 0 4 (13) 1 19 (59) 2 7 (22) 3 2 (6) Past attempt of complete ASM cessation No 9 (28) Yes 18 (56) Unknown 5 (16) ASM coindications Migraines 9 (28) Neuropathic pain 3 (9) Tremor 3 (9) Bipolar 1 (3) Current ASMs a Newer generation 25 (78) Older generation 7 (22) Number of previously tried ASMs 0 6 (19) 1 11 (35) 2 1 (3) 3 4 (13) 4 6 (19) 5 3 (10) Last provider seen Medical doctor 30 (94) Doctor of osteopathy 1 (3) Nurse practitioner 1 (3) Last provider seen specifically for seizures Epileptologist 25 (78) Nonepileptologist neurologist 4 (13) Non-neurologist 3 (9) Open in a new tab Abbreviations: ASM = antiseizure medication; JFK = John F. Kennedy University Medical Center/Hackensack Meridian School of Medicine; SUNY = State University of New York Downstate Health Sciences; UM = University of Michigan. Structural: traumatic brain injury (3), ischemic stroke (2), tumor (2), other (1), mesial temporal sclerosis (1), and cyst (1). a Antiseizure medications taken by more than 1 patient included levetiracetam (10), lamotrigine (9), carbamazepine (4), oxcarbazepine (3), lacosamide (3), and topiramate (2). Antiseizure medications taken by only 1 patient included clonazepam, zonisamide, phenobarbital, clobazam, perampanel, primidone, and valproate. There were no significant differences between responders and nonresponders (eTable 2). Perception of Seizure Risk and ASM Efficacy (eTable 3) Participants rated their two-year chance of another seizure on ASMs as a median 1 (IQR 0–2) on a scale of 0–10 with lower score being lower risk, compared with a median 5 (IQR 4–7) off ASMs ( Figure 2 ). Participants believed their ASMs to have a median efficacy of 9 (IQR 7–10) at preventing seizures (scale 0–10 with higher score being most effective). Figure 2. Patient Perception of Seizure Risk and ASM Efficacy. Open in a new tab (A) Each patient represents a dot, in which patients were asked what they think their chance of another seizure might be in the next 2 years off vs on their current ASMs. Superimposed lines signify different corresponding relative risks, e.g., all patients to the left of the RR = 6 line believed their risk off ASMs was more than 6 times their risk on ASMs. (B and C) We then show histograms for what relative or absolute risk increase would be implied by each response (dividing or subtracting responses). (D) Patients rated how effective they think their ASMs are on a 0–10 scale. ASM = antiseizure medication; RR = relative risk. Theme: High Confidence in ASMs Participants oftentimes believed that their risk of further seizures was zero on ASMs, and some believed that the risk would be zero even if they were to come off ASMs. Participants often believed that ASMs were completely protecting them from further seizures. Twelve (39%) rated their chance of another seizure as zero if they were to continue ASMs (with previous brain surgery: 6/11 [55%]; without previous brain surgery: 6/20 [30%]). Two (6%) believed that their chance would be zero even off ASMs. Ten (31%) believed that their ASMs were perfectly effective (response of 10 of 10). For example, a participant who had discontinued their ASMs after a tumor resection explained the following: I think the reason for the seizures is largely no longer present. (M51) Some of this complete confidence in ASMs seemed to relate to participant perception of physician counseling: Because one doctor told me, make sure you take your medicine, right? If you take the medicine the way you have to take it, you will never have a seizure anymore. (S15) Others believed that ASMs were perfectly effective because of personal experience of seizure cessation on starting ASMs, or a previous failed discontinuation attempt. For example, 1 participant with posttraumatic epilepsy and a past attempt at weaning levetiracetam indicated the following: It's so cut and dry and black and white with me that like I'm either on the medicine and I have no seizures or I’m off it and I have seizures like immediately. It has been a guaranteed situation. I know because I've experienced it firsthand if I'm not on the medication. (J52) Others felt similarly: It's just I'm on them, I don't have them. I go off it, I have them. Because the last time I tried coming off–the seizures came back. As long as I'm on the Tegretol, nothing happens. (M58) My trust is 100% in my pills … [because of past failed discontinuation attempts]. (J29) Minimal Clinically Important Difference Participants indicated that they would want their ASMs to be at least a median of 6 (IQR 4–9), effective to remain on ASMs (scale 0–10, higher being more effective) ( Figure 3 ). Figure 3. Patient Perception of Minimally Required ASM Efficacy to Justify Continuation. Open in a new tab ASM = antiseizure medication. Five participants (16%) would never accept weaning off ASMs (N = 5; 16%). Others would only wean off if it did not increase the risk of another seizure at all (N = 18; 56%) or only if it would not increase the risk of another seizure by “too much” (N = 8; 25%). One participant would wean off even if it increased the risk of another seizure by “a lot” (N = 1; 3%). (See eTable 4.) Theme: ASMs Would Be Worthwhile Even If Providing a Small Benefit Many participants believed that ASMs would still be worthwhile even if providing only a small benefit. This perspective partly depended on how the benefit was framed. Most participants indicated that an ASM would still be worthwhile if it decreased the number of seizures even if not to zero (N = 23; 72%), extended the time to the next seizure (N = 27; 84%), or reduced seizure severity (N = 21; 66%). Views on how much time an ASM would need to delay the next seizure to be worthwhile ranged from “any” (N = 5) to 2–6 months (N = 5) to 1–2 years (N = 4). Responses regarding acceptable relative risk increases ranged from 40% to 80%. Numerous participants would continue ASMs if there was any effect on seizures at all: I would take it if it reduced it any. Because that's the goal, right? You want to have hopefully none, but as least as possible, any percentage.. any number, any duration of time. (S2) If it took you know, say a … 3% chance of having a seizure and push it to negligible, that would have been sufficient. (M51) By contrast, 5 (16%) initially indicated that an ASM would be worthwhile only if it afforded complete seizure freedom: I would only want to take medication if it went to 0 seizures a year. Because driving. (M55) If it’s [seizure] an eventuality, what’s the point? (M50) However, when asked how much time an ASM would need to delay the next seizure to be worthwhile, participants with this initial reaction responded “any amount of time.” One participant (J29) initially indicated that an ASM would have to be at least 40% effective. Yet, when asked by how long an ASM would need to delay the next seizure to be worthwhile, the participant indicated any time at all, even a few days. Theme: Not All Participants Subscribed to the Task of Defining a Minimal Clinically Important Difference This theme was illustrated as follows: I'm laughing because you remind me of Lot and God when he kept bargaining to not destroy Sodom and Gomorrah. You can't bargain with God. What if it's this? What if it's that? (S14) Seizure Risk Tolerance Between 1 (not at all likely to come off ASMs) and 7 (extremely likely to come off ASMs), median responses were 5 (IQR 1–6) for the low-risk scenario (10% vs 11% two-year seizure risk on vs off ASMs), 1 (IQR 1–3) for the medium-risk scenario (10% vs 20%), and 1 (IQR 1–2) for the high-risk scenario (25% vs 50%) ( Figures 4 and 5 ). Among participants who answered both the low-risk and medium-risk pictographs, 14 (60%) were less likely to withdraw when shown the higher risks. Ten (34%) and 16 (70%) participants were less likely to withdraw when increasing from the medium-risk to high-risk pictographs and increasing from the low-risk to high-risk pictographs, respectively. (See eTable 5.) Figure 4. Pictograph Responses. Open in a new tab This figure shows the distribution of responses for each of the 3 pictographs. Each pictograph showed the participant a hypothetical 2-year seizure risk if the participant were to come off vs stay on antiseizure medications (e.g., 11% chance of another seizure vs 10% chance of another seizure). Participants then rated how likely they might be to agree to slowly taper off antiseizure medications if those hypothetical risks were true for them, on a scale from 1 to 7. Note that the “11% v 10%” pictograph had fewer responses than others. It was added after several interviews had already been completed, given numerous conservative responses to the 20% vs 10% scenario. This was to increase information regarding low-risk scenarios and establish a floor. Figure 5. Spaghetti Plot of Pictograph Responses. Open in a new tab Pictographs each depicted a different hypothetical 2-year chance of any more seizures if the patient were to come off vs remain on ASMs. In this plot, each colored line represents a respondent connecting their responses to each pictograph: the dark black line represents the mean, gray circles represent individual datapoints (with jitter for display), the x-axis displays the hypothetical seizure risks for each scenario, and the y-axis represents each patient's response to each scenario regarding how likely they might be come off ASMs if their seizure risks were as displayed in the x-axis. Distributions differed between pictographs (Kruskal-Wallis test p = 0.003; Jonckheere-Terpstra test for trend p < 0.001). ASM = antiseizure medication. Theme: Small Risk Differences Could Persuade Some Participants to Discontinue Representative explanations from participants who responded with “extremely likely” to come off medication in response to the low-risk scenario (10% vs 11%) included the following: That’s kind of like the same number to me. (J29) I'd have nothing to worry about if that's all that's changed. (J24) Several participants thus found small risk differences reassuring enough to justify discontinuation, further supported by current side effects (S11—memory problems; S8—bone health). One participant, currently on ASMs with a past temporal lobe operation, initially stated that even a 1% risk increase would be too much earlier in the interview. Cause even the 1%, go ahead [with taking the ASM] …the what if…oh my God, not a good thing. (J51) And yet, when shown the pictograph illustrating a 1% risk difference, he responded, That's a tough one…close call. That's not a big comparison, and responded ‘extremely likely’ to withdraw. (J51) Theme: However, Showing Risk Differences Could Also Dissuade Some Participants From Discontinuing Another participant (J22) with previous intracranial surgery planning to discontinue after 5 years of seizure freedom demonstrated the opposite response—initially favoring discontinuation, but discouraged when shown even small risks. Earlier in the interview, he indicated that a 5% postdiscontinuation risk would be too much. Accordingly, when shown the low-risk pictograph, he responded being extremely unlikely to withdraw if that were the case, despite plans to eventually withdraw. Theme: For Those Participants Who Would Continue ASMs Virtually No Matter How Small the Risks Might Be, Showing Risks Would Make Little Difference Seven participants (30%) responded no more favorably to the low-risk compared with the high-risk pictograph, indicating little sensitivity to the actual numbers being presented. Among participants who responded with “extremely unlikely” even to the low-risk pictograph, 1 participant explained their answer: If being on meds lowers my seizure chance, I'm staying on the meds. (M58) Another participant had been told by his providers that having any more seizures would mean having a tumor re-resection; thus, any extra risk would be perceived as too much: I know if I take my chances and I end up having a seizure, my life could be a risk. (J22) Even 1 participant (S13) who indicated that 10% vs 11% was “not much of a difference” still responded “extremely unlikely to wean off medication.” Qualitative responses described this reluctance. For example, 1 participant vividly recalled going into generalized convulsions when revving the engine of his car and then awakening in the hospital, several decades ago. Given transaminitis, sedation, and osteopenia on phenytoin, he switched to levetiracetam, with no subsequent perceived adverse effects or seizures. Now, regarding what seizure-free probability he would accept to consider withdrawing levetiracetam, he states, If the probability is 99.9%, I'd consider it. But if it was 90, I don't know. I can't imagine being responsible for injuring or killing someone. Unless there's certainty that you're not gonna have another seizure, I don't think it's worth it. (M52) Others likewise expressed unwillingness to withdraw if there was any possibility of another seizure: 'Cause even the 1%…the “what if” … You don’t want to fix something that’s not broke. (J51) I need to be 100% sure that this is not going to repeat itself, you know? So now I'm going to keep taking it. (J22) You could say oh you'll only have like a 10% chance of having a seizure. To me, that's 10 too much. … There's a lot of uncertainty that I wouldn't feel comfortable with just stopping. (J29) eTable 6 provides further data from the postinterview survey regarding agreement if their doctor were to suggest withdrawing ASMs, apart from any hypothetical scenario. Seizure Risk Counseling Theme: No Participant Recalled Having Received Numerical Seizure Risk Information, yet Most Want It While 22 respondents (69%) indicated that they recalled their epilepsy provider having any conversation regarding possibly discontinuing ASMs, none recalled having received any sort of numerical estimate of the chance of another seizure. Despite this, 16 (50%) indicated that they would like some sort of numbers from their provider. eTable 8 provides postinterview survey data, further supporting the desire for numerical counseling. (See eTable 7.) Theme: Personalized, Graphical Risk Information Seems Optimal Thirteen (41%) believed that pictographs would be extremely helpful if their doctor had such information tailored to their personal seizure risk, and 19 (59%) believed that they would be at least somewhat helpful to assist with decision making ( Table 2 ), enhance understanding of their condition, or better communicate recommendations to family: It's very it's very helpful. Math is not exactly one of my strongest suits. So, to see it in black and white, so to speak, as opposed to you know, numbers and percentages, that's helpful, very helpful. (S7) I'm a visual person. I like the visuals, good job. (M52) Table 2. How Helpful Would Seeing Pictographs Be in Clinical Practice If They Were Tailored to Participants' Personal Characteristics Were pictographs helpful? No. (%) 1—not at all 3 (9) 2 3 (9) 3 1 (3) 4 4 (13) 5 1 (3) 6 5 (16) 7–extremely 13 (41) No response a 2 (6) Open in a new tab a One patient was not asked the question because of interview time constraints. Another patient was asked but responded that having seizures was too scary to think about and, therefore, could not engage in the task of choosing numbers. Theme: However, Seizure Risk Information May Not Always Be Helpful One respondent (S3) indicated that seeing personalized pictographs would be “extremely helpful,” yet had difficulty articulating why (“Because they showed me that if you come, like, most of the people…let me see…how can I explain it?”). In addition, some participants were suspicious that the physician might intentionally elevate seizure risks to convince the participant to remain on ASMs (M50), worried that seizure risks are too random to predict (J29) or believed that only God knows what will happen (S14). Others believed that it was not a decision that could be answered with numbers or visuals, but rather based on a personal holistic judgment (S2). Finally, participants sometimes believed that no possible risk could be low enough, as above. One participant chose “extremely unlikely to withdraw” for all pictographs, explaining, I would never come off my medication. I need it. (S12) Discussion We conducted a mixed-methods study exploring issues surrounding seizure risk perception, tolerance, and counseling among patients with well-controlled epilepsy who might be candidates for ASM discontinuation. Participants generally had high confidence in their ASMs' ability to prevent seizures and often believed that downsides to ASMs were minimal and thus even small risk reductions from ASMs may justify their continued use. However, participants' reasoning regarding their perceived risk and minimal clinically important difference was highly variable. In addition, participants identified a lack of personalized seizure risk counseling as an important gap in care, which could be filled in many but not all circumstances by development of clinical decision support tools. Participants had strong beliefs in their ASM's efficacy, in many cases even that ASMs are 100% effective at preventing seizures or that their chance of another seizure is 0% on ASMs. This is understandable for a patient who is seizure free on ASMs or had a seizure after an attempted taper, and it is quite possible that ASMs have been highly effective for these patients. However, no ASM is likely to truly be 100% effective (literature suggests more modest effects 29 ), no risk is likely to be 0% even if continuing ASMs, and thus our interviews highlighted that many patients may have extreme risk perceptions because of thinking experientially rather than probabilistically. One patient summed this up when asked what their chance of another seizure might be on vs off ASMs—“Never thought of it that way.” In our sample, consequences worked in either direction, such as patients believing that tumor resection has definitively cured their seizure focus, thus an unrealistic sense of safety either way, or else patients demonstrating black-and-white thinking regarding inevitability of seizures off vs impossibility of seizures on ASMs. Either error could lead to decisions that are discordant with the patient's underlying values, had they possessed a more accurate understanding of their seizure susceptibility. At the very least, we believe that our data highlight that patients should be made more aware that ASMs are not perfectly protective against seizures, nor is another seizure guaranteed if they were to withdraw. Considerable past work outside the field of epilepsy has evaluated human perceptions of risks. For example, classic work explored judgmental heuristics in which people might erroneously evaluate probability (the chance of an event) based on “availability” (the ease by which they come to mind, influenced by the severity of an event if it were to occur). 36 , 37 This may lead a patient to incorrectly judge their chance of a postwithdrawal seizure as high, purely because their last seizure was severe, or in our case, patients may accordingly overestimate the risk reduction exerted by ASMs. Similarly, a clinician may become more risk averse or overestimate a patient's seizure recurrence risk if they have previously encountered patients with a severe postwithdrawal seizure recurrence (thus becoming more conservative with future treatments after experiencing a treatment complication). By contrast, people may underestimate probabilities of rare events, thinking that they are nearer to zero than they really are. 38 This was evident according to patients who estimated their risk of another seizure to be zero if they continued their current ASMs. Many participants provided intermediate responses regarding worthwhile relative risk reductions, e.g., approximately 50%. This is fairly similar to the effect of ASM continuation seen in clinical trials 4 , 30 and echoes the 50% responder rate oftentimes used as clinical trial outcomes. However, responses varied widely depending on how we asked the question. Many initially endorsed that they would require an ASM to guarantee no seizures to be worthwhile. Yet, patients, thereafter, nonetheless believed that an ASM would be worthwhile if it delayed the next seizure or reduced its severity by any amount, which are critical dimensions that existing seizure risk calculators lack. 12 , 39 Patients provided particularly extreme responses when asked in 2 specific ways, sometimes citing any delay in time as worthwhile or even a 1% absolute risk reduction, which are incongruent with the more liberal initial responses when asked regarding relative risk. We conjecture that perhaps patients have a more intuitive understanding of time, which can be felt as more concrete, than they do of probability, which can feel more abstract. Responses also seemed to vary depending on whether the risk was discussed verbally (“1%”) vs whether risks were shown in the pictograph, which to some patients seemed to minimize the risk (seeing the small difference) but for others seemed to magnify the risk (seeing that there is a difference, even if small). This emphasizes that simple differences in the format of how clinicians communicate risk can have profound consequences on patient understanding of that risk. While the aforementioned emphasizes that format and phrasing affect decisions, clearly the content of clinician recommendations and their level of concern also likely influence patient impressions. In our previous work, we asked clinicians what the maximal two-year postwithdrawal seizure recurrence risk they might tolerate and still consider withdrawal. Depending on the type of patient, average responses ranged from approximately 15% to 30%. 40 This somewhat mirrors results of this study in which patients became mostly unlikely to withdraw in the 20% and 50% scenarios. Still, other literature has shown some disconnect between patient and clinician priorities, such as patient decisions being significantly more influenced by adverse effects compared with neurologist decisions. 41 We are also currently conducting clinician focus groups in parallel with the patient-related work presented here regarding clinicians' impressions and fears surrounding ASM discontinuation. There is no universal answer as to what absolute risk difference should justify continuation, and it seems that for many patients, the correct clinical choice will be to continue ASMs long term. However, it seems unlikely that the threshold should be a 1% risk reduction or a >0% postwithdrawal risk, as conservatively endorsed by some of our participants. While our finding illustrates that patients perceive biopsychosocial consequences of seizures to be serious, we wonder whether patients may be underestimating harms from their ASMs. Presumably, even small medication-related harms could outweigh such a small benefit. ASM adverse effects include worsened mood 42 and cognition 43 and explain up to a quarter of variation in quality of life in seizure-free treated individuals. 44 Guidelines emphasize individualized discussions, necessitating understanding of both risks and benefits. Our data encourage continued development of seizure risk calculators. Existing literature 27 , 28 , 45 , 46 promotes visual representations of risks within well-defined time horizons, with presentation tailored to a patient's level of numeracy and literacy. Not only did we demonstrate receptivity to such communication tools but we also demonstrated that presenting risk may change decisions. One patient even specifically stated earlier in the interview that he could never accept even a 1% risk increase and yet interpreted this risk difference to be trivial when visualizing this difference in a pictograph. For those patients who would not tolerate withdrawal if there was any possibility of a seizure, it would also be critical to counsel that even ASM continuation does not guarantee seizure freedom. Moreover, even if seizure risk depiction might not affect decisions for some, such information was still cited as useful to enhance disease knowledge and explain treatment rationale to family. Still, our results also highlight limitations to using risk calculators in practice. Participants sometimes disregarded such information, given either holistic or spiritual rather than numerical decision-making processes, or else doubted such information's accuracy because of either high or low numeracy, or could not always understand such numerical information, or else appeared committed to continuing ASMs even if the risk reduction was small. A sample size of 32 limits generalizability or ability to compare responses between patient types. For example, despite a wide range of socioeconomic diversity and disease complexity, almost all patients in our sample had motor seizures impairing awareness and endorsed strong numeracy. However, qualitative work is valuable for its depth of information from a smaller number of key informants, and we do not believe that a larger sample size was necessary to achieve our qualitative study goals. Hypothetical responses may differ from actual responses if numerical counseling occurred in clinical encounters. Still, our experimental design allowed systematic hypothetical exploration across a range of possible seizure risks. Participants viewed their ASMs as highly effective, possibly some with an unrealistically high belief in treatment efficacy or unrealistically low belief in their chance of another seizure if continuing ASMs. Participants on average accepted approximately 50% relative risk reduction as a clinically meaningful effect to justify ASMs. However, some became much more likely to stay on medication when asked instead regarding absolute risk differences or time delay until the next seizure. Participants believed that visual depictions of individualized seizure risks would be helpful in routine clinical practice. However, for a subset of patients committed to continuing ASMs, numerical risk presentation would be unlikely to affect decision making. Future work will continue to assess patient decision-making factors surrounding ASM withdrawal beyond considerations of seizure risk and also engage clinician stakeholders for their perspectives regarding risk counseling. 47 Acknowledgment The authors thank the patients and caretakers who participated in this project. Footnotes Editorial, page e200482 Author Contributions S.W. Terman: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data; study concept or design; analysis or interpretation of data. J.M. Silva: major role in the acquisition of data. M. Kuster: major role in the acquisition of data. J. Lee: major role in the acquisition of data. A.P. Brand: major role in the acquisition of data. K. Manuel: major role in the acquisition of data. N. Kalia: major role in the acquisition of data; analysis or interpretation of data. M. Dugan: major role in the acquisition of data. M. Reid: major role in the acquisition of data. K. Mortati: major role in the acquisition of data. A. Tolmasov: major role in the acquisition of data. P.S. Patel: major role in the acquisition of data. J.F. Burke: drafting/revision of the manuscript for content, including medical writing for content; study concept or design; analysis or interpretation of data. A.C. Grant: drafting/revision of the manuscript for content, including medical writing for content. C.E. Hill: drafting/revision of the manuscript for content, including medical writing for content; study concept or design; analysis or interpretation of data. S.S. O'Kula: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data; study concept or design; analysis or interpretation of data. Study Funding This work was funded by the University of Michigan Department of Neurology internal funds. S.W. Terman was recently supported by an American Epilepsy Society Research and Training Fellowship for Clinicians. He is now supported by the NIH K23 AG081463. C.E. Hill is supported by NIH K23NS126495. Other authors report no relevant funding. Disclosure S.W. Terman has been a paid consultant for Jazz Pharmaceuticals and is currently a paid consultant for Xenon Pharmaceuticals for unrelated work. Full disclosure form information provided by the authors is available with the full text of this article at Neurology.org/cp . TAKE-HOME POINTS → We conducted a mixed-methods study exploring issues surrounding seizure risk perception, tolerance, and counseling among patients with well-controlled epilepsy who might be candidates for ASM discontinuation. → Participants generally believed that their ASMs were highly effective, sometimes even 100% seizure risk off ASMs but 0% risk on ASMs. → Participants believed that approximately 30%–50% relative risk reduction in seizures would make ASM continuation worthwhile, although participants responded more conservatively when asked regarding time to the next seizure. → Willingness to withdraw ASMs was moderate at very low risks and became more conservative when shown medium or higher seizure risks. → Respondents did not recall having received individualized seizure risk counseling yet would find such counseling useful in clinical practice. References 1. Jacoby A, Snape D, Baker GA. Determinants of quality of life in people with epilepsy. Neurol Clin. 2009;27(4):843-863. doi: 10.1016/j.ncl.2009.06.003 [ DOI ] [ PubMed ] [ Google Scholar ] 2. Hamilton KJ, Chen Z, Tomlin A, Kwan P. Mortality and morbidity of patients with treated and untreated epilepsy in New Zealand. Epilepsia. 2020;61(3):519-527. doi: 10.1111/epi.16435 [ DOI ] [ PubMed ] [ Google Scholar ] 3. Faught RE, Weiner JR, Guérin A, Cunnington MC, Duh MS. Impact of nonadherence to antiepileptic drugs on health care utilization and costs: findings from the RANSOM study. Epilepsia. 2009;50(3):501-509. doi: 10.1111/j.1528-1167.2008.01794.x [ DOI ] [ PubMed ] [ Google Scholar ] 4. Medical Research Council. Randomised study of antiepileptic drug withdrawal in patients in remission. Lancet. 1991;337(8751):1175-1180. doi: 10.1016/0140-6736(91)92856-w [ DOI ] [ PubMed ] [ Google Scholar ] 5. Perucca P, Gilliam FG. Adverse effects of antiepileptic drugs. Lancet Neurol. 2012;11(9):792-802. doi: 10.1016/S1474-4422(12)70153-9 [ DOI ] [ PubMed ] [ Google Scholar ] 6. Perucca P, Gilliam FG, Schmitz B. Epilepsy treatment as a predeterminant of psychosocial ill health. Epilepsy Behav. 2009;15(suppl 1):S46-S50. doi: 10.1016/j.yebeh.2009.03.016 [ DOI ] [ PubMed ] [ Google Scholar ] 7. Gilliam F. Optimizing health outcomes in active epilepsy. Neurology. 2002;58(8 suppl 5):S9-S20. doi: 10.1212/wnl.58.8_suppl_5.s9 [ DOI ] [ PubMed ] [ Google Scholar ] 8. Gilliam F, Carter J, Vahle V. Tolerability of antiseizure medications Implications for health outcomes. Neurology. 2004;63(10 suppl 4):S9-S12. doi: 10.1212/wnl.63.10_suppl_4.s9 [ DOI ] [ PubMed ] [ Google Scholar ] 9. St Louis EK. Minimizing AED adverse effects: improving quality of life in the interictal state in epilepsy care. Curr Neuropharmacol. 2009;7(2):106-114. doi: 10.2174/157015909788848857 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 10. Chen Z, Brodie MJ, Liew D, Kwan P. Treatment outcomes in patients with newly diagnosed epilepsy treated with established and new antiepileptic drugs A 30-year longitudinal cohort study. JAMA Neurol. 2018;75(3):279-286. doi: 10.1001/jamaneurol.2017.3949 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 11. Lamberink HJ, Otte WM, Geleijns K, Braun KPJ. Antiepileptic drug withdrawal in medically and surgically treated patients: a meta-analysis of seizure recurrence and systematic review of its predictors. Epileptic Disord. 2015;17(3):211-228. doi: 10.1684/epd.2015.0764 [ DOI ] [ PubMed ] [ Google Scholar ] 12. Lamberink HJ, Otte WM, Geerts AT, et al. Individualised prediction model of seizure recurrence and long-term outcomes after withdrawal of antiepileptic drugs in seizure-free patients: a systematic review and individual participant data meta-analysis. Lancet Neurol. 2017;16(7):523-531. doi: 10.1016/S1474-4422(17)30114-X [ DOI ] [ PubMed ] [ Google Scholar ] 13. Gloss D, Pargeon K, Pack A, et al. Antiseizure medication withdrawal in seizure-free patients: practice advisory update summary: report of the AAN guideline subcommittee. Neurology. 2021;97(23):1072-1081. doi: 10.1212/WNL.0000000000012944 [ DOI ] [ PubMed ] [ Google Scholar ] 14. Beghi E, Giussani G, Grosso S, et al. Withdrawal of antiepileptic drugs: guidelines of the Italian league against epilepsy. Epilepsia. 2013;54(suppl 7):2-12. doi: 10.1111/epi.12305 [ DOI ] [ PubMed ] [ Google Scholar ] 15. Terman SW, Aschmann HE, Hutton D, Burke JF. Best-worst scaling preferences among patients with well-controlled epilepsy: pilot results. PLoS One. 2023;18(3):e0282658. doi: 10.1371/journal.pone.0282658 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 16. Kilinç S, Campbell C. The experience of discontinuing antiepileptic drug treatment: an exploratory investigation. Seizure. 2008;17(6):505-513. doi: 10.1016/j.seizure.2008.01.002 [ DOI ] [ PubMed ] [ Google Scholar ] 17. Zhang Y, Coello PA, Brozek J, et al. Using patient values and preferences to inform the importance of health outcomes in practice guideline development following the GRADE approach. Health Qual Life Outcomes. 2017;15:1-10. doi: 10.1186/s12955-017-0621-0 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 18. American Academy of Neurology. Practice parameter: a guideline for discontinuing antiepileptic drugs in seizure-free patients -- summary statement. Report of the quality standards subcommittee of the American Academy of Neurology. Neurology. 1996;47:600-602. doi: 10.1212/wnl.47.2.600 [ DOI ] [ PubMed ] [ Google Scholar ] 19. Leeuw ED, Callegaro M, Hox J, Korendijk E, Lensvelt-Mulders G. The influence of advance letters on response in telephone surveys a meta-analysis. Public Opin Q. 2007;71(3):413-443. doi: 10.1093/poq/nfm014 [ DOI ] [ Google Scholar ] 20. Nakash RA, Hutton JL, Jørstad-Stein EC, Gates S, Lamb SE. Maximising response to postal questionnaires - a systematic review of randomised trials in health research. BMC Med Res Methodol. 2006;6:5. doi: 10.1186/1471-2288-6-5 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 21. Edwards PJ, Clarke MJ, Roberts I, et al. Methods to increase response to postal and electronic questionnaires. Cochrane Database Syst Rev. 2009;2009(3):MR000008. doi: 10.1002/14651858.MR000008.pub4 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 22. Poth CN, Creswell JW. Qualitative Inquiry and Research Design: Choosing Among Five Approaches. Fourth. SAGE Publications, Inc.; 2018. [ Google Scholar ] 23. Sandelowski M. Sample size in qualitative research. Res Nursing Health. 1995;18(2):179-183. doi: 10.1002/nur.4770180211 [ DOI ] [ PubMed ] [ Google Scholar ] 24. Guest G, Bunce A, Johnson L. How many interviews are enough?: an experiment with data saturation and variability. Field Methods. 2006;18(1):59-82. doi: 10.1177/1525822x05279903 [ DOI ] [ Google Scholar ] 25. Levitt HM, Motulsky SL, Wertz FJ, Morrow SL, Ponterotto JG. Recommendations for designing and reviewing qualitative research in psychology: promoting methodological integrity. Qual Psychol. 2017;4(1):2-22. doi: 10.1037/qup0000082 [ DOI ] [ Google Scholar ] 26. Hennink MM, Kaiser BN, Marconi VC. Code saturation versus meaning saturation: how many interviews are enough? Qual Health Res. 2017;27(4):591-608. doi: 10.1177/1049732316665344 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 27. Fagerlin A, Zikmund-Fisher BJ, Ubel PA. Helping patients decide: ten steps to better risk communication. J Natl Cancer Inst. 2011;103(19):1436-1443. doi: 10.1093/jnci/djr318 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 28. Bonner C, Trevena LJ, Gaissmaier W, et al. Current best practice for presenting probabilities in patient decision aids: fundamental principles. Med Decis Making. 2021;41(7):821-833. doi: 10.1177/0272989X21996328 [ DOI ] [ PubMed ] [ Google Scholar ] 29. Terman SW, Slinger G, Koek A, et al. Variation in seizure risk increases from antiseizure medication withdrawal among patients with well-controlled epilepsy: a pooled analysis. Epilepsia Open. 2024;9(1):333-344. doi: 10.1002/epi4.12880 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 30. Lossius MI, Hessen E, Mowinckel P, et al. Consequences of antiepileptic drug withdrawal: a randomized, double-blind study (Akershus Study). Epilepsia. 2008;49(3):455-463. doi: 10.1111/j.1528-1167.2007.01323.x [ DOI ] [ PubMed ] [ Google Scholar ] 31. Terman SW, Wang C, Wang L, et al. Reappraisal of the medical research council antiepileptic drug withdrawal study: contamination-adjusted and dose-response re-analysis. Epilepsia. 2022;63(7):1724-1735. doi: 10.1111/epi.17273 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 32. Horne R, Weinman J. Patients' beliefs about prescribed medicines and their role in adherence to treatment in chronic physical illness. J Psychosom Res. 1999;47(6):555-567. doi: 10.1016/s0022-3999(99)00057-4 [ DOI ] [ PubMed ] [ Google Scholar ] 33. Horne R, Weinman J, Hankins M, Horne R, Weinman J, Hankins M. The beliefs about medicines questionnaire: the development and evaluation of a new method for assessing the cognitive representation of medication. Psychol Health. 1999;14:1-24. doi: 10.1080/08870449908407311 [ DOI ] [ Google Scholar ] 34. Scherer LD, Zikmund-Fisher BJ. Eliciting medical maximizing-minimizing preferences with a single question: development and validation of the MM1. Med Decis Making. 2020;40(4):545-550. doi: 10.1177/0272989X20927700 [ DOI ] [ PubMed ] [ Google Scholar ] 35. McNaughton CD, Cavanaugh KL, Kripalani S, Rothman RL, Wallston KA. Validation of a short, 3-item version of the subjective numeracy scale. Med Decis Making. 2015;35(8):932-936. doi: 10.1177/0272989X15581800 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 36. Tversky A, Kahneman D. Availability: a heuristic for judging frequency and probability. Cogn Psychol. 1973;5(2):207-232. doi: 10.1016/0010-0285(73)90033-9 [ DOI ] [ Google Scholar ] 37. Tversky A, Kahneman D. Judgment under uncertainty: heuristics and biases. Science. 1974;185(4157):1124-1131. doi: 10.1126/science.185.4157.1124 [ DOI ] [ PubMed ] [ Google Scholar ] 38. Sundh J. Human behavior in the context of low-probability high-impact events. Humanities Soc Sci Commun. 2024;11:902-910. doi: 10.1057/s41599-024-03403-9 [ DOI ] [ Google Scholar ] 39. AED Withdrawal Risk Calculator. Accessed January 4, 2023. epilepsypredictiontools.info/aedwithdrawal [ Google Scholar ] 40. Terman SW, Slinger G, Rheaume CE, et al. Antiseizure medication withdrawal practice patterns: a survey among members of the American Academy of Neurology and EpiCARE. Neurol Clin Practice. 2023;13(1):e200109. doi: 10.1212/CPJ.0000000000200109 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 41. Ettinger AB, Carter JA, Rajagopalan K. Patient versus neurologist preferences: a discrete choice experiment for antiepileptic drug therapies. Epilepsy Behav. 2018;80:247-253. doi: 10.1016/j.yebeh.2018.01.025 [ DOI ] [ PubMed ] [ Google Scholar ] 42. Hessen E, Lossius MI, Reinvang I, Gjerstad L. Slight improvement in mood and irritability after antiepileptic drug withdrawal: a controlled study in patients on monotherapy. Epilepsy Behav. 2007;10(3):449-455. doi: 10.1016/j.yebeh.2007.01.014 [ DOI ] [ PubMed ] [ Google Scholar ] 43. Hessen E, Lossius MI, Gjerstad L. Antiepileptic monotherapy significantly impairs normative scores on common tests of executive functions. Acta Neurol Scand. 2009;119(3):194-198. doi: 10.1111/j.1600-0404.2008.01109.x [ DOI ] [ PubMed ] [ Google Scholar ] 44. Zou X, Hong Z, Chen J, Zhou D. Is antiepileptic drug withdrawal status related to quality of life in seizure-free adult patients with epilepsy? Epilepsy Behav. 2014;31:129-135. doi: 10.1016/j.yebeh.2013.11.028 [ DOI ] [ PubMed ] [ Google Scholar ] 45. Waldron C, Weijden TVanDer, Ludt S, Gallacher J, Elwyn G. What are effective strategies to communicate cardiovascular risk information to patients? A systematic review. Patient Educ Couns. 2011;82:169-181. doi: 10.1016/j.pec.2010.04.014 [ DOI ] [ PubMed ] [ Google Scholar ] 46. Trevena LJ, Bonner C, Okan Y, et al. Current challenges when using numbers in patient decision aids: advanced concepts. Med Decis Making. 2021;41(7):834-847. doi: 10.1177/0272989X21996342 [ DOI ] [ PubMed ] [ Google Scholar ] 47. Terman SW, van Griethuysen R, Rheaume CE, et al. Antiseizure medication withdrawal risk estimation and recommendations: a survey of American Academy of Neurology and EpiCARE members. Epilepsia Open. 2023;8(2):386-398. doi: 10.1002/epi4.12696 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Associated Data This section collects any data citations, data availability statements, or supplementary materials included in this article. Data Availability Statement Data can be shared on request and in compliance with required data use agreements. Articles from Neurology: Clinical Practice are provided here courtesy of American Academy of Neurology ACTIONS View on publisher site PDF (1.0 MB) Cite Collections Permalink RESOURCES Similar articles Cited by other articles Links to NCBI Databases Follow NCBI NCBI on X (formerly known as Twitter) NCBI on Facebook NCBI on LinkedIn NCBI on GitHub NCBI RSS feed Connect with NLM NLM on X (formerly known as Twitter) NLM on Facebook NLM on YouTube National Library of Medicine 8600 Rockville Pike Bethesda, MD 20894 Web Policies FOIA HHS Vulnerability Disclosure Help Accessibility Careers NLM NIH HHS USA.gov Back to Top

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