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Additional file 5. Primary end point analyses of mean and sum scores of FSS-9 at baseline and EOT12 Legends: The table displays the mean and sum scores of FSS-9 at baseline and EOT12 among participants who were included in the intention-to-treat and per-protocol analyses, respectively. The FSS-9 sum score ranges from 9 points, no fatigue, to 63 points, worst fatigue. Each item was ranged on a Likert scale from 1 point, no fatigue, to 7 points, worst fatigue. EOT12: 12 weeks after the end of treatment; SD: Standard deviation.

Additional file 2. The US-English and the Norwegian versions of the FSS-9. Legends: FSS-9; Nine-items Fatigue Severity Scale. All items in the FSS-9 are ranged as a Likert scale from 1 to 7, where 1 indicates “strongly disagree” and 7 indicates “strongly agree”.

Additional file 1. Norwegian national HCV treatment guidelines during the study period.

Additional file 7. A linear prediction of changes in FSS-9 sum scores from baseline to EOT12. Legends: The figure displays the linear predictionincluding 95 % confidence intervals of changes in FSS-9 sum scorefrom baseline to EOT12 for integrated and standard HCV treatment groups. EOT12: 12 weeks after the end of HCV treatment; FSS-9: Nine-item fatigue severity scale; HCV: Hepatitis C virus.

Additional file 3. The relationship between adults ADHD self-report scale version 1.1, part A (ASRS-A), and clinically diagnosed ADHD (presented by numbers in each category). Legends: ADHD: Attention-deficit/hyperactivity disorder; ASRS-A: The adults ADHD self-report scale version 1.1, part A. ASRS-A + and ASRS-A – were defined as exceeding and not reaching the symptom cutoff for at least four of six questions in the ASRS, part A, respectively. ADHD + and ADHD – were defined as being registered or not registered with a diagnosis of ADHD according to medical records. 1) A total of 10 patients were prescribed central stimulants. 2) A total of one patient was prescribed central stimulants. ASRS-A + and ADHD +: Spearman’s rho = 0.3130. Sensitivity = 29/36 = 0.806; Specificity = 117/189 = 0.619.

Additional file 12. Linear mixed model of the association between sociodemographic factors, injecting drug use, and drug use and FSS-9 sum score. Legends: The table displays a linear mixed model analysis regression of the impact of sociodemographic factors, injecting drug use, and drug use on FSS-9 sum scores at baseline and from baseline to EOT12in the study sample. The FSS-9 sum score ranges from 9 points, no fatigue, to 63 points, worst fatigue. “Educational attainment” was defined as the highest level of education completed. “Injecting substance use” was defined as having injected any substance at least once during the 12 months leading up to the first health assessment. Drug use was categorized according to the use during the past year. Frequent drug use was defined as consuming at least one of the drugs in the five drug classes more than weekly during the year leading up to the first health assessment. Participants who did not use drugs or used them less than weekly during the year were categorized as having “no frequent use of drugs”. Missing values were identified in 1.4% of FSS-9 scores, 1.1 % of educational attainment, 2.5 % of injecting drug use and 3.3 % of drug use at baseline and 29.9% of FSS-9 score at EOT12, and all were handled as “missing at random” and replaced with estimated values using expectation- maximization algorithm. Except for the “achieving SVR” predictor, we kept all the predictor variables constant at the baseline level in predicting changes in the FSS-9 sum scores from baseline to EOT12. To explore whether predictors predicted changes in the FSS-9 score from baseline to EOT12, the interaction between these factors and timeand EOT12) were added. EOT12: 12 weeks after the end of HCV treatment; FSS-9: Nine-item fatigue severity scale; HCV: Hepatitis C virus; SVR: Sustained virological response.

Additional file 8. Pen’s parades of FSS-9 sum scores at baseline and EOT12. Legends: The figures display participants who received integrated and standard HCV treatment and were included in the per-protocol analysis. The graphs demonstrate the FSS-9 sum scores at baseline/prior to the HCV treatment and EOT12. The red line represents the FSS-9 sum scores at baseline when the participants are in sorted order by FSS-9 sum scores to highestscore). The blue spikes demonstrate the FSS-9 sum score at EOT12. The length of the spikes mark the changes in the FSS-9 sum score from baseline to EOT12. Participants without spikes did not complete FSS-9 assessment at EOT12. The dotted line demonstrates the cut-off value for severe fatigue. EOT12: 12 weeks after the end of treatment; FSS-9: Nine-item Fatigue Severity Scale.

Additional file 2. Longitudinal ordinal multilevel mixed-effect logistic regression analysis of the association of ASRS–memory and –attention (combined outcome variable) with sociodemographic characteristics and substance use at baseline and over time (per year). Legends: ADHD: Attention-deficit/hyperactivity disorder; ASRS-A: The adults ADHD self-report scale version 1.1, part A. 1) The combined outcome variable was generated as a sum score of the responses to ASRS, part A, question 3 (ASRS–memory) and ASRS, part B, question 9 (ASRS–attention), ranged from 0 to 8. Patients who completed one health assessment visit and only responded to one of the two ASRS questions were excluded (n = 35). A total of 666 patients responded to ASRS–memory and attention questions. Of those, 241 had completed two or more occasions, rendering 257 repeated responses to the questions. The correlation between ASRS–memory and –attention questions was 0.39. ASRS–memory: How often do you have problems remembering appointments or obligations? ASRS–attention: How often do you have difficulty concentrating on what people say to you, even when they are speaking to you directly? The responses were answered on a Likert scale ranging from never (0) to very often (4) for each question, which generated a sum score from 0 to 8.

Additional file 4. Distribution of FSS-9 sum scores for integrated HCV treatmentand standard HCV treatmentgroups at baseline. Legends: The two graphsdisplay the FSS-9 sum scores for integrated HCV treatmentand standard HCV treatmentat baseline. The red lines demonstrate the distribution of the FSS-9 sum scores with skewness –0.8and –0.5and kurtoses 2.7 and 2.3. The FSS-9 sum scores ranges from 9 points, no fatigue, to 63 points, worst fatigue.

Additional file 1. US-English and Norwegian versions of the Adult ADHD self-report scale version 1.1, part A, and part B, question 9. Legends: ADHD: Attention-deficit/hyperactivity disorder.

Additional file 6. Linear mixed model of ΔFSS-9 sum score from baseline to EOT12 for integrated HCV treatment (per-protocol) (number of participants = 212, number of observations: 424). Legends: The table displays a linear mixed model analysis (Restricted Maximum Likelihood) regression of the impact of integrated HCV treatment on changes in FSS-9 sum scores (ΔFSS-9 sum scores) from baseline to EOT12 (per-protocol analysis), adjusted for acheiving SVR at EOT12. The FSS-9 sum score ranges from 9 points, no fatigue, to 63 points, worst fatigue. EOT12: 12 weeks after the end of HCV treatment; FSS-9: Nine-item fatigue severity scale.

Additional file 9. Linear mixed model of ΔFSS-9 sum scores from baseline to EOT12 for integrated HCV treatment (intention-totreat, sensitivity analysis without computed data), adjusted for SVR at EOT12 (number of participants = 189, number of observations: 378). Legends: The table displays a linear mixed model analysis (Restricted Maximum Likelihood) regression of the impact of integrated HCV treatment and SVR on changes in FSS-9 sum scores (ΔFSS-9 sum score) from baseline to EOT12 (intention-to-treat analysis without computed data by the expectation–maximization algorithm). The FSS-9 sum score ranges from 9 points, no fatigue, to 63 points, worst fatigue. EOT12: 12 weeks after the end of HCV treatment; FSS-9: Nine-item fatigue severity scale; SVR: Sustained virological response.

Additional file 3. Aspartate aminotransferase to platelet ratio index. Legends: The figure displays the equation to calculate APRI score. AST upper limit of normal range was defined as 45 IU/Land 35 IU/L.

Additional file 10. Linear mixed model of ΔFSS-9 sum scores from baseline to EOT12 for integrated HCV treatment, adjusted for SVR . Legends: The table displays a linear mixed model analysis regression of the impact of integrated HCV treatment and SVR on changes in FSS-9 sum scoresfrom baseline to EOT12. The FSS-9 sum score ranges from 9 points, no fatigue, to 63 points, worst fatigue. EOT12: 12 weeks after the end of HCV treatment; FSS-9: Nine-item fatigue severity scale; SVR: Sustained virological response.

Bakgrunn: Metadonsubstitusjon er anbefalt for behandling av opioidavhengighet. En betydelig inter-individuell variasjon i metadons daglige doser og oppnådde serumkonsentrasjoner er rapportert. Mulige underliggende årsaker er imidlertid ikke fullt ut forstått. Formålet med denne forskningen var å undersøke om genetiske, pato-fysiologiske og farmakologiske faktorer kan påvirke metadon serumkonsentrasjon-dose-ratio (CDR), og å utforske sammenhengen mellom serumkonsentrasjon og kliniske utfall i metadon substitusjonsbehandling. Metoder: Dette prosjektet har brukt observasjonsdata fra tre forskjellige kilder, inkludert to retrospektive laboratoriedatabaser av terapeutisk legemiddelovervåking (artiklene I og II), og en prospektiv kohortdatabase om pasienter under substitusjonsbehandling med metadon (artiklene III og IV). Lineær regresjon analysemetode ble brukt for å undersøke effekten av CYP genetiske polymorfismer (artikkel I), alder, kjønn og samtidig behandling med andre legemidler (artikkel II), samt leverfibrose og BMI (artikkel III) på metadon CDR. Sammenhengen mellom metadon serumkonsentrasjon og subjektive abstinenssymptomer og bivirkninger ble også undersøkt (artikkel IV). Resultater: Artikkel I: Homozygote bærere av CYP2B6*6 hadde signifikant høyere metadon CDR sammenlignet med ikke-bærere (P < 0.001). Artikkel II: Kvinner hadde sammenlignet med menn 9 % lavere CDR, mens denne ratioen ikke var påvirket av alder. Samtidig medisinering med CYP induserende legemidler reduserte metadon CDR med 36 %, mens CYP3A4 hemmende legemidler økte denne med 36 %. Artikkel III: Det var ingen signifikant sammenheng mellom CDR og leverfibrose (koeffisient: 0.70; 95% KI: -2.16, 3.57; P: 0.631) eller cirrhose (-0.50; -4.59, 3.59; 0.810) sammenlignet med ingen/begrenset fibrose. Deltakerne med en BMI på 25-30 kg/m² hadde høyere CDR (2.34; 0.22, 4.45; 0.031) sammenlignet med de som hadde lavere BMI. Artikkel IV: Total SOWS-score (P < 0,001), de spesifikke subjektive abstinenssymptomene angst (P = 0.004), ben- og muskelsmerter (P = 0.003), rastløshet (P = 0.017) og (i lavere grad) skjelving (P = 0.046), også bruk av heroin (P = 0.015) og alkohol (P = 0.011) var assosiert med lavere metadonkonsentrasjoner i serum. Cannabisbruk var (i lavere gard) relatert til høyere serumkonsentrasjoner av metadon (P = 0.049). Konklusjon: Våre forskningsfunn viser at genetiske polymorfismer i CYP2B6, kjønn, BMI og samtidig behandling med CYP induserende og/eller CYP3A4 hemmende legemidler kan forklare noen av variasjonene i dosejusterte serumkonsentrasjoner av metadon. Alder, grad av leverfibrose og andre CYP polymorfismer ser ikke ut til å være assosiert med metadon CDR. Vi har også funnet assosiasjoner mellom subjektive opioidabstinenssymptomer samt rusmiddelbruk, og metadonkonsentrasjoner i serum. Våre funn bekrefter dagens kliniske og forskningsmessige utfordringer knyttet til metadonbehandling med tanke på en stor intra-individuell variasjon i legemiddelets farmakokinetikk. Resultatene er også i tråd med tidligere forskning som viser at metabolismen av metadon kan bli påvirket av flere faktorer. Samlet sett støtter vår forskning viktigheten av en individuelt tilpasset dosering basert på mulige involverte faktorer og selvopplevde opioidabstinenssymptomer for å oppnå en tilstrekkelig og ønsket serumkonsentrasjon som kan redusere tilbakefall til rusmiddelbruk med tilhørende risiko og for å optimalisere behandlingen. Background: Methadone maintenance treatment (MMT) is recommended for the treatment of opioid addiction. A considerable inter-individual variability in methadone daily doses and serum concentrations has been reported; however, the underlying causes are not fully understood. The aim of this thesis was to investigate the influence of genetic, pathophysiological and pharmacological factors on serum methadone concentration-to-dose ratio (CDR), and to explore the relationship between serum methadone concentration and clinical outcomes in MMT. Methods: The thesis has used observational data from three different sources including two retrospective laboratory databases on therapeutic drug monitoring (TDM) (papers I and II), and a prospective cohort data on patients undergoing MMT (papers III and IV). Linear mixed model analyses were used to investigate the impact of CYP genetic polymorphisms (paper I), age, gender and co-medication (paper II), as well as liver fibrosis and BMI (paper III) on methadone CDR. Association between serum methadone concentrations and subjective symptoms of withdrawal and adverse effects were also investigated (paper IV). Results: Paper I: The homozygous carriers of CYP2B6*6 had significantly higher methadone CDR compared with non-carriers (P < 0.001). Paper II: Women as compared to men had 9% lower CDR, whereas the ratio was not influenced by age. Concomitant medication with CYP inducers reduced methadone CDR by 36%, whereas CYP3A4 inhibitors increased it by 36%. Paper III: There was no significant relationship between CDR and liver fibrosis (coefficient: 0.70; 95% CI: -2.16, 3.57; P: 0.631) or cirrhosis (-0.50; -4.59, 3.59; 0.810) compared to no/limited fibrosis. Participants with a BMI of 25-30 kg/m² had higher CDR (2.34; 0.22, 4.45; 0.031) compared with those who had lower BMI. Paper IV: The total SOWS score (P < 0.001); the specific subjective withdrawal symptoms of anxiety (P = 0.004), bone and muscle aches (P = 0.003), restlessness (P = 0.017), and (slightly) shaking (P = 0.046), also use of heroin (P = 0.015) and alcohol (P = 0.011) were associated with lower methadone concentrations. Cannabis use was slightly related to higher methadone concentrations (P = 0.049). Conclusion: This thesis demonstrates that genetic polymorphisms in CYP2B6, gender, BMI and concurrent medication with CYP inducers and CYP3A4 inhibitors may explain some of the variations in dose-adjusted serum methadone concentrations. Age, degree of liver fibrosis and the other CYP polymorphisms do not seem to be associated with methadone CDR. Additionally; we have shown associations between the subjective opioid withdrawal symptoms as well as substance use, and serum methadone concentrations. Our findings confirm the current clinical and research challenges in MMT regarding a large intra-individual variability in methadone pharmacokinetics and influence of several factors. The thesis supports the importance of an individually tailored dosage based on the possible factors involved and self-perceived opioid withdrawal symptoms to achieve the desired serum methadone concentration. This is crucial to reduce relapse to substance use with associated risks and to optimize the treatment outcomes. Doktorgradsavhandling

Additional file 2 Adjusted linear mixed model for the Substance Use Severity Index (SUSI) for patients with two or more SUSI measurements (N = 170). CI: Confidence Interval; OAT: Opioid Agonist Therapy; cSUSI: Mean Change in Substance Use Severity Index; SUD: Substance Use Disorder. 1) The SUSI is a continuous variable ranging from 0 to 1, where 0 indicates no substance use and 1 indicates daily substance use for all substances (cannabis, amphetamines, cocaine, opioids, benzodiazepines, and alcohol). 2) The value shows the difference in adjusted SUSI between “going to inpatient detoxification” and “not going to inpatient detoxification” at baseline (before detoxification). 3) Interpretation: the cSUSI per year from baseline of a constant predictor and its comparator (e.g., the cSUSI of “ongoing injecting substance use” (constant predictor) and “no ongoing inject substance use” (constant comparator) per year from baseline). 4) Interpretation: the cSUSI of a time-varying predictor and its time-varying comparator per year from baseline (e.g., the cSUSI per year of “going to inpatient detoxification” and “not going to inpatient detoxification” from baseline). The table displays a linear mixed model analysis (Restricted Maximum Likelihood regression) evaluating the impact of inpatient intoxication, injecting substance use, age, and gender on the SUSI at baseline and from baseline (over time) among patients undergoing outpatient SUD treatment with two or more substance use measurements.

Additional file 3. STROBE Statement. Checklist of items that should be included in reports of cohort studies

Additional file 1. STROBE Statement. Checklist of items that should be included in reports of cohort studies.

Additional file 5. Mean (SD) item scores for single items on the FSS-9 at baseline and follow-up. Legend: FSS-9: Nine-item Fatigue Severity Scale; I: Item; OAT: Opioid agonist therapy; SD: Standard Deviation. Follow-up: The FSS-9 score on the last health assessment during the study period among patients with two or more annual health assessments. Mean (SD) item scores for single items on the FSS-9 for patients using methadone or buprenorphine as OAT opioid.

Additional file 3. Aspartate aminotransferase to platelet ratio index (APRI). Description: APRI: Aspartate aminotransferase to platelet ratio index. The figure displays the APRI score equation. The AST upper limit of normal range was defined as 45 IU/L (male) and 35 IU/L (female).

Additional file 4. Potential correlations between sociodemographic and clinical factors and fatigue. The figure shows that potential sociodemographic and clinical comorbidities may affect fatigue among patients with substance use disorders.

Additional file 6. Linear mixed model of fatigue (FSS-9) adjusted for sociodemographic and clinical factors among patients receiving methadone as an OAT opioid at baseline (N = 209). Legends: APRI: Aspartate transaminase to platelet ratio index; CI: Confidence interval; CRP: C-reactive protein; FSS-9: Nine-item Fatigue Severity Scale; eGFR: estimated glomerular filtration rate; HIV: Human Immunodeficiency virus; kPa: Kilopascal; OAT: Opioid Agonist Therapy. 1) Age per 10 years was centred according to mean age (43 years) in the study sample at baseline. 2) Includes amphetamine or cocaine use. The OAT opioid ratio: a ratio between the received dose of OAT opioids per day divided by the expected mean dose of OAT opioids (buprenorphine 18 mg, buprenorphine-naloxone 18/4.5 mg or methadone 90 mg). The educational level: highest level of education was coded 0–4 with 4 as the highest educational level. Unstable housing situation: living on the street, homeless shelter, or with family and friends at any time in the past 30 days prior to the health assessment. Debt difficulties: struggling with repaying current illegal and legal debt. Injecting substance use: Having injected a substance in the past 12 months prior to the health assessment. Frequent use of substances: at least weekly during the past 12 months prior to the health assessment. Viral load of HCV: From − 0.5 to 0.5, where the range ≥ − 0.5 to 0 identifies the high viral load (HCV PCR ≥ 800,000 IE/ml). Zero (0) defined patients without HCV infection. When using the Bonferroni corrected p-values (αaltered = 0.05 / 43 = 0.0012), the predictors did not affect the FSS-9 sum score significantly. The table displays a linear mixed model analysis (Restricted Maximum Likelihood regression) evaluating sociodemographic and clinical factors’ (predictors) changes in the FSS-9 sum score at baseline and their influence on changes in the FSS-9 sum score (time trend) per year from baseline among patients receiving methadone as an OAT opioid. The predictors’ effect estimates and time trends estimate adjusted mean differences in the FSS-9 sum score.

Additional file 4. Equations to calculate diazepam equivalents. Legends: Equations used to calculate lowest, mean, and highest equipotency dose of included benzodiazepines and z-hypnotics.

Additional file 2. The US-English and the Norwegian versions of FSS-9. Description: Legends: FSS-9; Nine-item Fatigue Severity Scale. All items in the FSS-9 are ranged as a Likert scale from 1 to 7, where 1 indicates “strongly disagree” and 7 “strongly agree”.

Additional file 3. Opioid agonist therapy and hepatitis C treatment in Norway and Sweden

Additional file 1. The number of months from baseline to the second or third health assessment. No.: Number of patients; SD: Standard deviation; ref.: Reference. The table displays the number of patients with one, two, and three health assessments, including a nine-item Fatigue Severity Scale score. The table displays the time between baseline and the second and third health assessments.

Additional file 7. Linear mixed model of fatigue (FSS-9) adjusted for sociodemographic and clinical factors among patients receiving buprenorphine as an OAT opioid at baseline (N = 321). Legends: APRI: Aspartate transaminase to platelet ratio index; CI: Confidence interval; CRP: C-reactive protein; FSS-9: Nine-item Fatigue Severity Scale; eGFR: estimated glomerular filtration rate; HIV: Human Immunodeficiency virus; kPa: Kilopascal; OAT: Opioid Agonist Therapy. 1) Age per 10 years was centred according to mean age (43 years) in the study sample at baseline. 2) Includes amphetamine or cocaine use. The OAT opioid ratio: a ratio between the received dose of OAT opioids per day divided by the expected mean dose of OAT opioids (buprenorphine 18 mg, buprenorphine-naloxone 18/4.5 mg or methadone 90 mg). The educational level: highest level of education was coded 0–4 with 4 as the highest educational level. Unstable housing situation: living on the street, homeless shelter, or with family and friends at any time during the past 30 days prior to the health assessment. Debt difficulties: struggling with repaying current illegal and legal debt. Injecting substance use: Having injected a substance during the past 12 months prior to the health assessment. Frequent use of substances: at least weekly during the past 12 months prior to the health assessment. Viral load of HCV: From − 0.5 to 0.5, where the range ≥ − 0.5 to 0 identifies the high viral load (HCV PCR ≥ 800,000 IE/ml). Zero (0) defined patients without HCV infection. When using the Bonferroni corrected p-values (αaltered = 0.05 / 43 = 0.0012), the predictors did not affect the FSS-9 sum score significantly. The table displays a linear mixed model analysis (Restricted Maximum Likelihood regression) evaluating sociodemographic and clinical factors’ (predictors) changes in the FSS-9 sum score at baseline and their influence on changes in the FSS-9 sum score (time trend) per year from baseline among patients receiving buprenorphine as an OAT opioid. The predictors’ effect estimates and time trends estimate adjusted mean differences in the FSS-9 sum score.

Additional file 1. Methodology description: estimating chronic hepatitis C (HCV) prevalence among people on opioid agonist therapy (OAT) in Norway and Sweden

Assessed articles, references and cross-references, excluded duplicates. (PDF 1228 kb)

Comprehensive details of the search strategy. (PDF 274 kb)

PRISMA Checklist 2009. (PDF 424 kb)

CONSORT 2010. Evaluation of design, conduct, analysis, and interpretation, and the validity of the results in included RCTs. (PDF 357 kb)

CONSORT 2010. Evaluation of design, conduct, analysis, and interpretation, and the validity of the results in included RCTs. (PDF 357 kb)

Newcastle-Ottawa scale. Assessment of the quality of included cohort studies. (PDF 427 kb)