POS0123 NEUROPATHIC PAIN SYMPTOMS IN INFLAMMATORY HAND OSTEOARTHRITIS(OA) LOWERS HEALTH RELATED PHYSICAL QUALITY OF LIFE AND MAY REQUIRE ANOTHER APPROACH THAN ANTI-INFLAMMATORY TREATMENT

Background:

Pain is a common, difficult to manage symptom in hand osteoarthritis (OA). Multiple pain mechanisms may play a role in hand OA.

Objectives:

To investigate presence of neuropathic pain symptoms in patients with inflammatory hand OA, characteristics of those patients, their impact on health related quality of life (HR-QoL), and the influence of anti-inflammatory treatment on neuropathic pain symptoms.

Methods:

Data from a randomised, double-blind, placebo-controlled trial of prednisolone including 92 patients with hand OA fulfilling ACR criteria were used. At baseline patients had signs of synovial inflammation, a VAS finger pain of ≥30 mm and who flared ≥20 mm upon NSAID washout. The primary endpoint was VAS finger pain (0-100) at week 6.

Neuropathic pain symptoms were measured at baseline and week 6 using the validated painDETECT questionnaire, consisting of questions on pain quality, pain intensity over time and radiating pain. Scores range -1 to 38 and patients are classified as having unlikely (<13), indeterminate (13-18) and likely (>18) neuropathic pain. HR-QoL was measured with physical component scale (PCS) of Short-Form 36 (SF36; 0-100), comorbidities with the Self-administered Comorbidities Questionnaire (SCQ; 0-45), radiographic severity with Kellgren-Lawrence (KL) sum score (0-120), and treatment response with OMERACT-OARSI responder criteria.

Association of patient characteristics with neuropathic pain symptoms was analysed with univariate and multivariate ordinal logistic regression, with painDETECT as dependent variable. Association of neuropathic pain symptoms with HR-QoL was analysed with multivariate linear regression, adjusted for age, sex, BMI, VAS finger pain, SCQ score and KL sum score, with PCS as dependent variable. Response of neuropathic pain symptoms and VAS pain to prednisolone was analysed with generalised estimating equations. Association of neuropathic pain symptoms at baseline with response to treatment was analysed using χ2-tests and GEE.

Results:

91 patients had complete painDETECT data at baseline (mean painDETECT score 12.8 [SD 5.9]). Scores were <13 in 53%, 13-18 in 31% and >18 in 16%. Higher painDETECT score categories were associated with less radiographic damage, more comorbidities, female sex and higher VAS finger pain in multivariate analysis. (table 1)

Table 1.

Ordinal logistic regression with painDETECT categories as dependent variable

VariablesMean (SD) N=91 (100%)Odds ratio (95% CI)Age64 (9)0.96 (0.90 to 1.02)Female sex; N (%)72 (79%)3.84 (1.19 to 12.39)*BMI; median (SD)27 (24 to 29)0.97 (0.89 to 1.06)SCQ score; median (SD)2 (1 to 5)1.04 (1.04 to 1.36)*VAS finger pain53.8 (2.1)1.02 (1.00 to 1.04)*KL sum score37 (16)0.96 (0.93 to 1.00)*

*p<0.05. BMI = body mass index. SCQ = Self-administered comorbidities questionnaire. VAS = visual analog scale. KL= Kellgren-Lawrence.

Patients with painDETECT scores >18 had a lower HR-QoL (PCS -6.5 [95%CI -10.4 to -2.6]) than those with painDETECT scores <13.

PainDETECT scores remained unchanged throughout the trial in both prednisolone-treated and placebo-treated patients, and there was no between-group difference at week 6. VAS pain improved more in the prednisolone group than in the placebo group (mean between-group difference -16.5 [95%CI -26.1 to -6.9]) (figure 1). No association between the presence of neuropathic pain symptoms at baseline and OMERACT-OARSI response to treatment was found.

Conclusion:

Patients with inflammatory hand OA and additional neuropathic pain symptoms are more often female and have more comorbidities, and report a lower QoL, than those without. Neuropathic pain symptoms seem unresponsive to anti-inflammatory therapy. Clinicians should be aware of neuropathic pain symptoms in their patients as they might benefit from additional, specific treatment.

Acknowledgements:

The authors thank all patients for their participation in the HOPE study, and participating rheumatologists for inclusion of patients in the HOPE study. We also thank research nurses B.A.M.J. van Schie-Geyer and S. Wongsodihardjo, and technicians J.C. Kwekkeboom and E.I.H. van der Voort, for their contributions.

Disclosure of Interests:

Coen van der Meulen: None declared, Lotte van de Stadt: None declared, Féline Kroon: None declared, Marion Kortekaas: None declared, Annelies Boonen Speakers bureau: Lecture for UCB; paid to department., Consultant of: Yes. Advisory board meetings at Galapagos, Eli Lilly and Abvvie; paid to department., Grant/research support from: Yes. Grants by Celgene and Abbvie; paid to department., Stefan Böhringer: None declared, Marieke Niesters: None declared, Monique Reijnierse: None declared, Frits Rosendaal: None declared, Naghmeh Riyazi: None declared, M. Starmans: None declared, Franktien Turkstra: None declared, Jende van Zeben: None declared, Cornelia Allaart: None declared, Margreet Kloppenburg Consultant of: For Abbvie, Pfizer, Levicept, GlaxoSmithKline, Merck-Serono, Kiniksa, Flexìon, Galapagos, Jansen, CHDR and local investigator of industry-driven trial (Abbvie). All fees were paid to the institution., Grant/research support from: Grant by the Dutch Arthritis Society

POS0258 REAL-TIME VERSUS STATIC SCORING IN MUSCULOSKELETAL ULTRASONOGRAPHY IN PATIENTS WITH INFLAMMATORY HAND OSTEOARTHRITIS

Background:

Ultrasound (US) is used in rheumatic musculoskeletal diseases (RMDs) such as hand osteoarthritis (OA) as outcome measure. Traditionally scoring is performed real-time, but central reading of static US images could avoid issues of inter-rater reliability. However, agreement between real-time and static assessment has not been studied

Objectives:

To study the agreement between real-time and static scoring of US in inflammatory hand OA.

Methods:

Ultrasound was performed of 30 joints obtained in 75 patients with hand osteoarthritis, treated with prednisolone or placebo in a randomized double-blind trial. Hand joints were assessed for synovial thickening, effusion, Doppler signal and osteophytes by ultrasound (score 0-3 per joint) at baseline and after treatment. Two ultrasonographers blinded for clinical data scored the live images together (simultaneously) in real-time. A consensus score for each joint was recorded. Representative images stored during scanning were scored by one ultrasonographer minimally 6 months after real-time scoring. For each patient, images of each visit were scored paired, with known chronological order.

Agreement between scoring methods was studied at joint level with quadratic weighted kappa. At patient level, intra-class correlations (ICC; mixed effect model, absolute agreement, with clustering taken into account) were calculated at both timepoints. ICCs were also calculated for the delta of sum scores. Responsiveness of scoring methods was analyzed with generalized estimating equations (GEE) with treatment as independent and ultrasonography findings as dependent variable.

Results:

Thirty-nine patients (52%) were treated with prednisolone and 36 (48%) were treated with placebo. Patient characteristics were well-balanced between treatment groups.

All patients had signs of synovial thickening and osteophytes as assessed by real-time ultrasonography, and almost all signs of effusion (99%) or a positive Doppler signal (95%) in at least one joint. Total ultrasonography sum score for osteophytes was high (mean 45 ±SD 12), whereas sum score was low for positive Doppler signal (mean 5.9 ±SD 4.4), with intermediate sum scores for synovial thickening and effusion (mean 16 ±SD 6.3 and 11 ±SD 6.0 respectively). Static sum scores were overall slightly higher (osteophytes mean 48 ±SD 10; Doppler mean 6.9 S±D 5.0; synovial thickening mean 20 ±SD 7.0 and effusion 13 ±SD 6.5)

Agreement at baseline was good to excellent at joint level (kappa 0.72-0.88) and moderate to excellent at patient level (ICC 0.59-0.86). Agreement for delta sum scores was poor to fair for synovial thickening and effusion (ICC 0.18 and 0.34 respectively), but excellent for Doppler signal (ICC 0.80) (Table 1).

Real-time ultrasonography showed responsiveness to prednisolone with a mean between-group difference of synovial thickening sum score of -2.5 (CI:-4.7 to-0.3). Static ultrasonography did not show a decrease in synovial thickening (Figure 1). No difference in ultrasonography scores was seen for the other ultrasonography features, neither with real-time nor static scoring.

Conclusion:

While cross-sectional agreement between real-time and static ultrasonography was good, agreement of delta sum scores was not and paired static ultrasonography measurement of synovial thickening did not show responsiveness to prednisone therapy where real-time ultrasonography did. Therefore, when using ultrasonography in clinical trials, real-time dynamic scoring should remain the standard.

Table 1.

Agreement on patient level

BaselineWeek 6Delta W6-BLICC (95% CI)ICC (95% CI)ICC (95% CI)Synovitis0.59 (0.26-0.76)0.58 (0.24-0.77)0.18 (0 - 0.40)Effusion0.84 (0.66-0.92)0.84 (0.75-0.89)0.34 (0.12-0.53)Osteophytes0.82 (0.50-0.92)0.78 (0.56-0.88)NDDoppler0.86 (0.75-0.92)0.91 (0.85-0.94)0.80 (0.70 -0.87)

ICC: intra-class correlation coefficient linear mixed model (random patient, fixed rating), absolute agreement. ND: Not Dertermined

Disclosure of Interests:

Lotte van de Stadt: None declared, Féline Kroon: None declared, Monique Reijnierse Grant/research support from: Dutch Arthritis Foundation, Désirée van der Heijde Consultant of: bbVie, Amgen, Astellas, AstraZeneca, Bayer, BMS, Boehringer Ingelheim, Celgene, Cyxone, Daiichi, Eisai, Eli-Lilly, Galapagos, Gilead, Glaxo-Smith-Kline, Janssen, Merck, Novartis, Pfizer, Regeneron, Roche, Sanofi, Takeda, UCB Pharma, Frits Rosendaal: None declared, Naghmeh Riyazi: None declared, R. de Slegte: None declared, Jende van Zeben: None declared, Cornelia Allaart: None declared, Margreet Kloppenburg Consultant of: Abbvie, Pfizer, Levicept, GlaxoSmithKline, Merck-Serono, Kiniksa, Flexion, Galapagos, Jansen, CHDR, Grant/research support from: MI-APPROACH, Marion Kortekaas: None declared

POS1087 USING LIPIDOMICS TO PREDICT PREDNISOLONE TREATMENT RESPONSE IN PATIENTS WITH INFLAMMATORY HAND OSTEOARTHRITIS: THE HOPE STUDY

Background:

Lipidomics analysis has become a valuable technology for understanding patho-physiological mechanisms and may aid the identification of biomarkers of therapeutic responsiveness.

Objectives:

To explore the use of lipidomics for prediction of prednisolone treatment response in patients with inflammatory hand osteoarthritis.

Methods:

The Hand Osteoarthritis Prednisolone Efficacy (HOPE) study is a blinded, randomized placebo-controlled trial, that investigated the effect of prednisolone treatment in patients with painful, inflammatory hand OA, fulfilling the American College of Rheumatology criteria. The present analyses comprised only patients randomized to daily 10 mg prednisolone treatment for six weeks. Response to prednisolone treatment was defined according to the OARSI-OMERACT responder criteria at six weeks. Baseline blood samples were obtained non-fasted. Lipid species were quantified in erythrocytes with the LipidyzerTM platform (Sciex). After pre-processing of the data, 286 lipids species were available for further analyses (nmol/mL). In addition, we used an in-house LC-MS/MS platform to analyse oxylipins in plasma, identifying 25 oxylipins (area ratios). Elastic net regularized regression was used to predict prednisolone treatment response. A 10-fold cross-validation (CV) was performed for selection of the optimal tuning parameters based on the smallest CV mean prediction error. First, a model was fit with commonly assessed patient characteristics and patient reported outcomes, measured at baseline (model 1). Second, we fitted model 2 by adding the LipidyzerTM platform lipids to model 1. Third, we fitted model 3 by adding the oxylipins to model 1. The discriminatory accuracy of the model was estimated by receiver operating characteristic (ROC) analyses. The area under the curve (AUC) and corresponding 95% confidence intervals (CI) were calculated using 1,000 bootstrap replications.

Results:

Among the 40 patients included, 31 (78%) fulfilled the OARSI-OMERACT responder criteria. From the included general patient characteristics (Table 1), elastic net selected baseline hand function as only predictor of treatment response, with an AUC of 0.78 (95% CI 0.60;0.96) (Figure 1). In model 2, we added the 286 LipidyzerTM platform variables to model 1. In addition to hand function, two lipids were selected: diacylglycerol(DAG)(16:0/16:0) and phosphatidylethanolamine(PE)(O-18:0/20:4), which improved the discriminatory accuracy to an AUC of 0.92 (0.83;1.02). Lastly, model 3 was fit with patient characteristics as well as oxylipins, resulting in selection of AUSCAN function and three oxylipin predictors: 9-hydroxy-octadecatrienoic acid (HOTrE), 5-hydroxy-eicosapentaenoic acid (HEPE) and 10-hydroxy-docosahexaenoic acid (HDHA), with an AUC of 0.85 (0.69;1.02).

Conclusion:

The patients’ lipid profile improved the discriminative accuracy of the prediction of prednisolone treatment response in patients with inflammatory hand osteoarthritis compared to prediction by commonly measured patient characteristics alone. This exploratory study suggests that lipidomics is a promising field for biomarker discovery for prediction of anti-inflammatory treatment response.

Table 1.

Baseline characteristics

All prednisolone treatedn = 40Respondersn = 31 (78%)Non-respondersn = 9 (23%)General characteristicsAge, year62.4 (9.3)62.9 (9.4)60.8 (9.4)Sex, % women858489BMI, kg/m227.4 (4.4)27.8 (4.2)26.2 (5.0)Education, % high464256Disease duration6.7 (7.1)7.2 (7.4)4.9 (5.8)Erosive OA, %717456Kellgren-Lawrence sum score, 0-12035.1 (16.4)34.1 (16.5)37.5 (14.7)Ultrasound synovitis sum score, 0-9016.2 (6.6)15.5 (6.4)18.7 (7.2)VAS global assessment, 0-10052.3 (20.6)54.2 (16.8)45.6 (30.8)AUSCAN pain, 0-2011.0 (3.3)11.3 (2.4)10 (5.4)AUSCAN function, 0-3617.7 (7.6)19.6 (6.6)11 (7.5)

Numbers represent mean (SD) unless otherwise specified. AUSCAN = Australian/Canadian Hand Osteoarthritis Index, BMI = body mass index, VAS = visual analogue scale

Disclosure of Interests:

Marieke Loef: None declared, Tariq Faquih: None declared, Johannes von Hegedus: None declared, Mohan Ghorasaini: None declared, Andreea Ioan-Facsinay: None declared, Féline Kroon: None declared, Martin Giera Shareholder of: Pfizer, Consultant of: Boehringer Ingelheim Pharma, Margreet Kloppenburg: None declared.

POS0182 MINIMAL CLINICALLY IMPORTANT IMPROVEMENT (MCII) AND PATIENT ACCEPTABLE SYMPTOM STATE (PASS) FOR PAIN AND FUNCTION INSTRUMENTS IN HAND OSTEOARTHRITIS (OA)

Background:

Australian/Canadian Hand OA Index (AUSCAN), Michigan Hand Outcomes Questionnaire (MHQ), Functional Index of Hand OA (FIHOA) and visual analogue scale (VAS) are frequently used instruments to measure pain and function in hand OA research. MCII and PASS are useful to interpret results of patient reported outcomes.

Objectives:

To estimate MCII and PASS for these instruments using anchor-based methods.

Methods:

Hand OA patients participating in a six-week randomised placebo-controlled trial with prednisolone (RCT; NTR5263) and those attending the two-year follow-up visit of the observational Hand OSTeoArthritiS cohort completed AUSCAN subscales pain and function, MHQ subscales pain, activities of daily living (ADL) and overall function, FIHOA and 100mm VAS pain. RCT participants were asked to indicate whether they changed compared to baseline (improved/no change/worse) and to rate the importance of improvement (very much/moderately/slightly/not at all). MCII was defined as the minimal improvement in symptoms achieved by 75% of participants who stated a slight/moderate improvement during the RCT, calculated as the 75th percentile of the distribution of change scores from baseline in this group. Absolute and relative percentage change were evaluated. For MCII direction of effect was unified, so positive values indicate worse symptoms and vice versa. Participants from both studies rated satisfaction with their state of health (acceptable/unacceptable). PASS was defined as the minimal score considered acceptable for 75% of participants, calculated as the 75th percentile of the distribution of scores in participants who rated their health ‘acceptable’.

Results:

Demographics of the RCT (n=92, mean age 63.9, 79% women) and cohort (n=383, 60.9 years, 84% women) participants were typical for hand OA. RCT participants were more symptomatic (e.g. mean [SD] VAS pain 54.0 [20.5] versus 35.2 [19.1]). Of the function instruments, only AUSCAN had a credible MCII (relative percentage improvement 9.8%), while the (positive) MCII values for FIHOA and MHQ subscales would indicate that worsening was rated as functional improvement (table 1). MCII was negative (corresponding to improvement) for all pain instruments, with relative percentage change around 25% for VAS and MHQ, compared to only 2% for AUSCAN. PASS values of all instruments were comparable in the two populations. Most instruments had a PASS around 50% of the possible maximum score, except for MHQ ADL, in which higher is better and a relatively high PASS is thus indicative of a floor effect (table 1).

Conclusion:

The only function instrument with an acceptable threshold for MCII was AUSCAN function, while for pain MHQ and VAS performed better than AUSCAN. PASS values show a relatively high level of tolerance of 50% of the maximum of the scale.

Table 1.

MCII and PASS of pain and function instruments in hand OA patients in two settings.

MCII (95% CI) in RCT†PASS (95% CI)InstrumentAbsolute unitsPercentage[n]RCT (n=68)Cohort (n=126)MHQ Overall function, 0-100*3.4 (-2.7;9.5)3.6 (-9.1;16.3)[23]55.6 (52.6;58.5)48.1 (45.7;50.4) ADL, 0-100*1.6 (-4.4;7.6)2.8 (-9.6;15.3)[23]71.7 (68.2;75.1)62.9 (59.8;66.0) Pain, 0-100-12.2 (-17.2;-7.1)-23.1 (-35.4;-10.8)[16]47.0 (40.5;53.5)55.7 (52.0;59.5)AUSCAN Function, 0-36-3.3 (-5.7;-0.9)-9.8 (-23.9;4.2)[23]17.1 (15.3;19.0)20.9 (19.4;22.3) Pain, 0-20-1.1 (-2.6;0.4)-1.8 (-18.5;14.9)[27]9.0 (8.2;9.9)11.1 (10.3;11.8)FIHOA, 0-300.1 (-1.6;1.7)22.7 (-0.7;46.0)[23]12.4 (11.1;13.7)13.9 (12.8;15.0)VAS pain, 0-100-11.5 (-18.2;-4.7)-24.4 (-36.1;-12.8)[27]47.7 (42.2;53.3)48.8 (44.6;53.0)

Direction of effect of all instruments is higher is worse, except those with *.

†For all MCII direction of effect was unified, so positive values indicate worse symptoms and negative values values indicate improved symptoms.

Disclosure of Interests:

Féline Kroon: None declared, Lotte van de Stadt Grant/research support from: The HOSTAS and HOPE studies were sponsored by the Dutch Arthritis Society., Désirée van der Heijde: None declared, Margreet Kloppenburg Grant/research support from: The HOSTAS and HOPE studies were sponsored by the Dutch Arthritis Society.

POS0371 BIOLOGICAL REPRODUCIBILITY OF TARGETED LIPIDOME ANALYSES IN PLASMA AND ERYTHROCYTES OVER A 6-WEEK PERIOD

Background:

Lipidomics analysis has become a valuable technology for understanding patho-physiological mechanisms and the identification of candidate biomarkers in rheumatic musculoskeletal disorders. Variability in within-subject repeated measurements may lead to bias towards the null when estimating the association between biomarkers and a disease or treatment. Hence, information regarding the stability of the metabolite levels over time is essential.

Objectives:

We aimed to assess the lipid composition and biological reproducibility of lipid measurements in plasma and erythrocytes.

Methods:

Plasma and erythrocyte samples from 42 osteoarthritis patients (77% women, mean age 65 years, mean BMI 27 kg/m2), obtained non-fasted at baseline and six weeks, were used for the quantitative measurement of up to 1000 lipid species across 13 lipid classes with the LipidyzerTM platform in nmol/mL. Data was processed based on the relative standard deviation of quality controls, taking batch effects into account. Intraclass correlation coefficients (ICCs) and corresponding 95% confidence intervals (CI) were calculated to investigate the variability of the lipid concentrations between timepoints. The ICC distribution of lipid metabolites in plasma and erythrocytes were compared using two-sided paired Wilcoxon tests.

Results:

We measured 778 lipids in plasma, compared to 916 lipids in erythrocytes. After data processing, the analyses included 630 lipids in plasma, and 286 in erythrocytes. From these, 243 lipids overlapped between sample types. Major differences were observed between the sample types in the number of lipids per lipid class and the total concentration of the lipids within a class. Triacylglycerols (TAG) and cholesteryl esters (CE) were more abundant in plasma. Conversely, phosphatidylethanolamines (PE), sphingomyelins (SM) and ceramides (CER) were less abundant in plasma compared to erythrocytes (table 1). In plasma 78% of lipid measurements were good to excellently reproduced, with an overall median ICC 0.69. Compared to plasma, a considerably lower amount (35%) of lipids were well reproduced in erythrocytes. Median reproducibility of lipids in erythrocytes was 0.51. Figure 1 shows the ICC score distribution in plasma with erythrocytes, with a significantly better reproducibility in plasma (p-value<0.001). However, while overall reproducibility was better in plasma, this was not observed for all lipid classes. At class-level, reproducibility in plasma was superior for TAGs and CEs, while CERs, DAGs, (L)PEs and SMs showed better reproducibility in erythrocytes.

Table 1.

Number of individual lipids per class and class concentrations in plasma and erythrocytes

PlasmaErythrocytesNumber of lipid speciesClass concentration (nmol/mL)Number of lipid speciesClass concentration (nmol/mL)Triacylglycerols4821579.4 (1064.9-3195.2)1346.5 (5.6-9.4)Diacylglycerols913.3 (8.4-22.2)105.8 (4.7-6.2)Free fatty acids20745.3 (552.0-1202.9)20486.9 (379.2-669.2)Cholesteryl esters244571.6 (4065.1-5521.3)51.2 (0.9-1.7)Phosphatidylcholines314013.7 (3203.1-4661.6)423899.2 (3723.0-4296.6)Phosphatidylethanolamines26156.2 (120.9-180.3)423954.6 (3721.9-4323.3)Lysophosphatidylcholines9385.9 (335.6-442.9)7119.8 (109.7-168.9)Lysophosphatidylethanolamines24.2 (3.5-4.9)48.6 (6.8-9.7)Sphingomyelins121204.6 (1037.0-1351.9)82695.8 (2434.8-2815.6)Ceramides614.1 (11.9-17.4)7163.0 (133.3-186.4)Dihydroceramides21.0 (0.8-1.3)11.8 (1.4-2.1)Hexosylceramides55.1 (4.7-5.9)45.6 (5.0-7.4)Lactosylceramides23.4 (2.7-3.8)223.8 (20.6-33.5)

Numbers represent median (interquartile range) unless otherwise specified. Data represents baseline measurements.

Conclusion:

In plasma biological reproducibility was good for most lipid measurements. Although overall reproducibility was better in plasma compared to erythrocytes, notable differences were observed at individual- and lipid class-level that may favour the use of a particular sample type.

Disclosure of Interests:

Marieke Loef: None declared, Johannes von Hegedus: None declared, Mohan Ghorasaini: None declared, Féline Kroon: None declared, Martin Giera Shareholder of: Pfizer, Consultant of: Boehringer Ingelheim Pharma, Andreea Ioan-Facsinay: None declared, Margreet Kloppenburg: None declared

Presence and absence of non-native fish species in the Wet Tropics region, Australia

Distributional records of non-native fish species were identified in the Wet Tropics region, Far North Queensland, Australia, through a compilation of published records and expert knowledge. A total of 1106 records were identified comprising 346 presence and four uncertain records for at least 13 species, and 756 absence records. All current presence records consist of six species from the families Cichlidae and Poeciliidae with established self-sustaining populations in the region, probably affecting the highly diverse native fish fauna.

Substitution of didanosine sachets by chewable tablets: a pharmacokinetic study in patients with AIDS

We have conducted a pharmacokinetic study of didanosine (ddI), formulated in sachets and in tablets, in patients with acquired immune deficiency syndrome (AIDS). Fifteen subjects received 250 or 167 mg of ddI twice daily as the sachet formulation and used this for at least 1 month. Subsequently, the patients were converted to receive ddI chewable/dispersible tablets (250-mg sachets to 200-mg tablets; 167-mg sachets to 125-mg tablets). Four subjects withdrew because of clinical deterioration or adverse effects. Serial blood samples were collected for pharmacokinetic monitoring during the use of the sachets and after 1 month of use of the tablets. No statistically significant differences were found in the maximum plasma concentration (Cmax), the time to reach Cmax (tmax), the area under the plasma concentration-time curve (AUC), or the terminal elimination half-life (t1/2) between the two formulations. Patients who received low-dose ddI (sachets, 167 mg; tablets, 125 mg) displayed lower plasma concentrations than did the patients receiving high-dose ddI (sachets, 250 mg; tablets, 200 mg), despite an equal weight-normalized dose of ddI in these two groups.