Despite frequent interchangeability in industry parlance, persistence and adherence are fundamentally different metrics that serve distinct purposes in pharmaceutical strategy.
Adherence measures how closely patients follow prescribed dosing regimens once on therapy—it captures whether patients take their medicine correctly, but not whether they continue taking it at all. A patient can be 100% adherent to yesterday's dose but no longer on therapy.
Persistence specifically tracks how long patients remain on treatment after initiation—essentially measuring when they drop off entirely. This distinction is crucial: while adherence might fluctuate over time, persistence loss represents a definitive endpoint for revenue generation. Once a patient discontinues, the economic relationship is severed.
Current industry measurement typically captures adherence through pharmacy refill data (medication possession ratios, proportion of days covered), but persistence requires longitudinal tracking across the entire treatment journey—a capability many pharmaceutical companies lack with traditional analytics approaches.
The data reveals striking patterns across chronic diseases that should concern every pharmaceutical executive responsible for brand or franchise performance:
HIV Treatment: Among antiretroviral therapies, real-world evidence shows that 50% or fewer patients remain on treatment after 12 months across all studied regimens in US Medicare populations [2]. Pre-exposure prophylaxis (PrEP) demonstrates even more concerning patterns, with substantial discontinuation challenges across diverse global populations [3,4].
GLP-1 Receptor Agonists: Despite their breakthrough status, real-world persistence rates vary dramatically by indication and formulation. For diabetes treatment, 12-month persistence ranges from 45-70% depending on the specific agent [5,6]. Among US commercially insured adults using GLP-1RAs for weight management without diabetes, persistence rates show significant early discontinuation patterns, with many patients stopping within the first six months [7].
Psoriasis Biologics: Real-world data from US healthcare claims databases revealed wide variation in persistence rates, with differences of up to 45 percentage points between best and worst performing agents within the same therapeutic class [8]. This translates directly to competitive advantage for superior-performing brands.
Multiple Sclerosis: Disease-modifying treatments show variable persistence patterns, with newer agents like ocrelizumab demonstrating relatively higher persistence compared to traditional therapies, though healthcare resource utilization remains substantial even among persistent patients [9].
These figures aren't academic curiosities—they're directly correlated with revenue forecasting accuracy and brand value creation.
That’s a €30M delta—for the same drug, same price, same patient base. The only difference? How long they stay.
This isn’t about compliance theory. It’s direct revenue at stake.
To provide pharmaceutical executives with actionable benchmarking data, the following table consolidates real-world persistence rates across major chronic disease categories. These figures represent the best available evidence from recent peer-reviewed studies and should inform commercial forecasting and competitive positioning strategies.
| Therapeutic Area | Condition / Treatment | 6-Month Persistence | 12-Month Persistence | 24-Month Persistence | Key Notes | Source |
|---|---|---|---|---|---|---|
| Endocrinology | GLP-1 RAs (Diabetes) | 55-75% | 45-70% | 35-55% | Higher rates with oral formulations | [5,6] |
| GLP-1 RAs (Weight Mgmt) | 40-60% | 30-45% | - | Significant early discontinuation | [7] | |
| Hyperuricemia/Gout | - | 54.4% | - | Higher with comorbid HTN (76.8%) | [12] | |
| Neurology | Multiple Sclerosis (Oral DMTs) | - | 74.6% | - | Pooled analysis, 25.4% discontinuation | [13] |
| Multiple Sclerosis (Ocrelizumab) | - | 80-85% | 75-80% | Higher persistence vs traditional DMTs | [9] | |
| Rheumatology | Rheumatoid Arthritis (Biologics) | - | 70-85% | 60-75% | Wide variation by agent | [14] |
| RA (Disease Mgmt Programs) | - | 89.3% | - | vs 59.4% standard care | [14] | |
| Psoriasis (Biologics) | 60-85% | 55-80% | 45-70% | 45% difference between best/worst | [8] | |
| Infectious Disease | HIV (Antiretroviral) | - | ≤50% | - | Medicare population data | [2] |
| HIV PrEP | 40-60% | 30-50% | - | Varies by population/setting | [3,4] | |
| Bone Health | Osteoporosis (Teriparatide) | 65-75% | 60-70% | 55-65% | Twice-weekly formulation | [15] |
| Osteoporosis (Bisphosphonates) | 70-80% | 65-75% | 55-65% | Annual dosing shows higher rates | [15] | |
| Mental Health | Depression (Antidepressants) | 60-70%* | 45-60%* | 35-50%* | *Industry estimates | [16] |
| Cardiovascular | Hypertension (ACE/ARBs) | 75-85%* | 65-75%* | 55-65%* | *Industry estimates | [16] |
| Statins | 70-80%* | 60-70%* | 50-60%* | *Industry estimates | [16] |
Table Notes:
- Ranges reflect variation across studies, populations, and specific agents within therapeutic classes
- Dash (-) indicates insufficient data available from current literature
- Asterisk (*) indicates industry estimates where specific peer-reviewed data was limited
- Persistence rates generally decline over time across all therapeutic areas
- Patient support programs can improve persistence by 15-30% in most categories
This data reveals several critical insights for pharmaceutical strategy:
Therapeutic Class Variations: Persistence rates vary dramatically even within the same indication, suggesting that formulation, dosing frequency, and side effect profiles significantly impact patient retention.
Time-Dependent Decay: All therapeutic areas show consistent decline in persistence over time, with the steepest drops typically occurring in the first 6-12 months post-initiation.
Intervention Opportunities: The substantial improvements seen with disease management programs (89.3% vs 59.4% in rheumatology) demonstrate that systematic patient support can meaningfully impact persistence rates.
Competitive Differentiation: The 45 percentage point spread in psoriasis biologics persistence rates illustrates how persistence can become a significant competitive advantage within crowded therapeutic markets.
The business implications extend far beyond simple patient acquisition costs. McKinsey & Company estimates that medication non-adherence costs the pharmaceutical industry €188–290 billion annually in the United States alone. For individual brands, the impact is even more stark.
Consider an illustrative calculation for a specialty therapy with these parameters:
At first glance, a 40% discontinuation rate translates to approximately €48 million in lost annual revenue potential for each cohort (illustrative calculation).
Yet this figure only scratches the surface. Persistence is not a linear metric: to calculate the true financial impact, one would need at least monthly data. The timing of discontinuation is critical. A sharp drop in month one devastates revenue far more severely than the same drop occurring in month nine—even if both scenarios show the same 12-month persistence percentage.
These calculations remain estimations, but they highlight a structural blind spot in many forecasting models. Traditional approaches rarely account for the exponential decay that emerges in real-world persistence data. For chronic therapies, where lifetime treatment value depends on continuity, the cumulative losses compound dramatically over time.
This is also reshaping payer negotiations. Persistence metrics are increasingly becoming the differentiator between preferred and non-preferred status. Insurers are shifting rebate structures to reward manufacturers who can demonstrate measurable persistence improvements—a trend set to accelerate as healthcare systems demand clear ROI from every therapeutic decision.
The pharmaceutical industry's persistence measurement capabilities remain remarkably primitive compared to the sophistication required for effective brand management. Most teams rely on quarterly, static Excel dashboards created 3-6 months after treatment initiation—missing critical early warning signals that could enable intervention.
The typical process involves:
This approach essentially treats persistence as a lagging indicator—something to be reported rather than actively managed. The 3-6 month reporting delay means patient cohorts have already completed their natural discontinuation cycle by the time data becomes available.
Moreover, current systems provide almost no insight into the mechanisms driving persistence failures. Are patients switching to competitors? Experiencing side effects? Dissatisfied with efficacy? The data doesn't exist to guide targeted commercial interventions.
Forward-thinking pharmaceutical brands are implementing advanced analytics that treat persistence as a dynamic, measurable, and actionable commercial lever. Rather than relying on retrospective reports, they're building near-real-time monitoring systems that can track patient journeys across the entire treatment lifecycle.
Permea Insight Hub represents this next generation of pharmaceutical analytics—a configurable platform specifically designed for the unique needs of pharma brand teams. Unlike traditional business intelligence tools, Permea provides dynamic, real-world insights that enable proactive persistence management.
The breakthrough comes from combining three critical data streams:
This creates a comprehensive view that reveals persistence patterns in the context of commercial activities—enabling evidence-based intervention strategies that directly impact brand performance.
Permea's Persistence Widget specifically addresses the limitations that plague current industry approaches:
Monthly Drop-off Tracking provides granular visibility into when patients discontinue, enabling intervention before revenue loss occurs. Rather than discovering discontinuation patterns months later, brand teams can identify at-risk cohorts within 60-90 days of initiation.
Dynamic Cohort Segmentation allows brands to differentiate treatment-naïve patients from those switching from competitors—critical intelligence for understanding market dynamics and tailoring retention strategies.
Timeframe Comparisons enable precise measurement of campaign impact on persistence rates. Brand teams can correlate specific marketing initiatives with improved long-term patient retention—a direct linkage to lifetime value creation.
Competitive Benchmarking reveals not only whether a brand retains patients, but precisely which competitors capture switched patients and when—actionable intelligence for commercial strategy refinement.
The application of advanced persistence analytics creates several distinct competitive advantages:
Patient Population Optimization allows brands to identify sub-populations with naturally higher persistence rates, enabling more effective targeting and resource allocation. For example, analysis of GLP-1 therapies has revealed that specific patient characteristics correlate with 20-30% higher persistence at 12 months—targeting insights that fundamentally change acquisition strategy.
Early Warning System Implementation enables intervention before revenue loss occurs. By identifying persistence drop-off at 60-90 days (when intervention can still influence behavior), brands have successfully reduced discontinuation rates by 15-20% through targeted patient support programs.
Campaign Impact Measurement provides real feedback on commercial activities' persistence effects. Rather than measuring only prescription volume, companies can now correlate specific marketing initiatives with improved long-term patient retention.
Market Share Evolution Analysis tracks not just initial prescription capture, but the entire patient journey including switching patterns and competitive dynamics over time.
Seeing drop-off is only step one. Here’s what leading teams do next:
With Insight Hub, you can go from passive persistence reports to real-time, behavior-informed action plans. That’s how brands stop silent churn—and start building retention strategies that stick.
If your launch or brand strategy doesn’t yet include persistence curves by cohort and time window, there’s a gap in your story.
Temedica’s Insight Hub brings that story to life—fast, flexible, and ready to plug into your planning cycle.
👉 Book a walk-through now and see how quickly your team can go from blind spots to behavior-based insight.
[1] Gleason PP, Urick BY, Marshall VD, Friedlander S, Qiu F, Leslie RS. Real-world persistence and adherence to glucagon-like peptide-1 receptor agonists among obese commercially insured adults without diabetes. J Manag Care Spec Pharm. 2024;30(7):123-132.
[2] Li A, Prajapati G, Geng EH, Ladage VP, Arduino RC, Watson M, Gross R, Doshi JA. Antiretroviral Treatment Gaps and Adherence Among People with HIV in the U.S. Medicare Program. AIDS Behav. 2024;28(4):1123-1134.
[3] Anyasi J, Idemudia E, Badru T, et al. Discontinuation of HIV oral pre-exposure prophylaxis: findings from programmatic surveillance within two general population HIV programs in Nigeria. BMC Public Health. 2024;24(1):1456.
[4] Rao A, Mhlophe H, Comins CA, et al. Persistence on oral pre-exposure prophylaxis (PrEP) among female sex workers in eThekwini, South Africa, 2016-2020. PLoS One. 2022;17(4):e0265434.
[5] Conti A, Pontiggia S, Vergani V, et al. Comparing medication persistence with oral and subcutaneous semaglutide in a real-world setting. Acta Diabetol. 2025;62(2):245-253.
[6] Kassem L, Khalaila R, Stein N, Saliba W, Zaina A. Efficacy, adherence and persistence of various glucagon-like peptide-1 agonists: nationwide real-life data. Diabetes Obes Metab. 2024;26(8):3234-3242.
[7] Xu H, Carrero JJ, Chang AR, et al. Titration and discontinuation of semaglutide for weight management in commercially insured US adults. Obesity (Silver Spring). 2025;33(2):312-320.
[8] Leonardi C, Zhu B, Malatestinic WN, et al. Real-World Biologic Adherence, Persistence, and Monotherapy Comparisons in US Patients with Psoriasis: Results from IBM MarketScan. Adv Ther. 2022;39(7):3203-3222.
[9] Moccia M, Affinito G, Berera G, et al. Persistence, adherence, healthcare resource utilization and costs for ocrelizumab in the real-world of the Campania Region of Italy. J Neurol. 2022;269(12):6234-6244.
[10] McKinsey & Company. Improving patient adherence through data-driven insights. December 2018. Available at: https://www.mckinsey.com/industries/life-sciences/our-insights/improving-patient-adherence-through-data-driven-insights
[11] Rao SK. How Medication Non-Adherence Impacts Brand Management. Pharmaceutical Executive. March 2021. Available at: https://www.pharmexec.com/view/how-medication-non-adherence-impacts-brand-management
[12] Akari S, Nakamura Y, Furusawa J, Miyazaki T, Kario K. The reality of treatment for hyperuricemia and gout in Japan: A historical cohort study using health insurance claims data. J Clin Hypertens. 2022;24(11):1539-1547.
[13] Nicholas JA, Edwards NC, Edwards RA, et al. Real-world adherence to, and persistence with, once- and twice-daily oral disease-modifying drugs in patients with multiple sclerosis: a systematic review and meta-analysis. BMC Neurol. 2020;20(1):281.
[14] Ebina K, Etani Y, Maeda Y, et al. Drug retention of biologics and Janus kinase inhibitors in patients with rheumatoid arthritis: the ANSWER cohort study. RMD Open. 2023;9(2):e003160.
[15] Fujita R, Endo T, Takahata M, et al. Real-world persistence of twice-weekly teriparatide and factors associated with the discontinuation in patients with osteoporosis. J Bone Miner Metab. 2022;40(5):782-789.
[16] Industry estimates compiled from multiple sources including pharmacy benefit management reports and therapeutic area analyses. Specific citations available upon request.