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You have full access to this open access article. Studies in drug use settings rarely use sex under the influence of drugs as an indicator of sexual risk behaviors. This study explored the prevalence of sex under the influence of drugs and its correlates among people who use drugs PWUD in Cambodia. We included PWUD from 12 provinces in this study. A multiple logistic regression analysis was conducted to identify factors associated with sex under the influence of drugs. Of the total, After adjustment, sex under the influence of drugs was significantly associated with living in urban areas AOR 2. This study documents the high prevalence of sex under the influence of drugs and its risk factors among male and female PWUD in Cambodia. These findings point to the need for integrating HIV and harm-reduction programs using innovative approaches to address the overlapping risks in this key population. People who use drugs PWUD , including people who inject drugs, are highly exposed to sexual risk behaviors, such as sex under the influence of drugs. Sex under the influence of drugs is defined as sexual intercourse when a partner is intoxicated with one of the drugs, including heroin, cannabis, amphetamines, cocaine, and benzodiazepines Ding et al. This behavior puts PWUD at a higher risk of the human immunodeficiency virus HIV and other sexually transmitted infections than the general population Armstrong et al. Therefore, prevention and reduction of sex under the influence of drugs have the potential to ameliorate the HIV epidemic and improve the health of this key population. Globally, studies on the association between drug use and sexual risk behaviors among HIV key populations tend to focus more on transactional and condomless sex than sex under the influence of drugs. For instance, a street-intercept survey of adults in two inner-city communities with a high HIV prevalence in the United States showed that people who used crack cocaine were more likely to trade sex for money or drugs than people who did not use drugs Baseman et al. A study among young African American men who have sex with men documented a positive association between drug use before sexual activity and inconsistent condom use or multiple sexual partnerships Browne et al. In the same manner, another study showed that the increase in severity of drug use had a positive association with the increased frequency of unprotected sex among American men in substance use treatment Newville et al. A few other studies looked at sex under the influence of drugs as a risk factor of sexual risk behaviors. The authors explained that, under the influence of drugs, a partner would lose judgment and proper decision-making on or negotiation for safe sex. The high prevalence of sex under the influence of drugs among PWUD deserves further research given its strong association with sexual risk behaviors and the limited number of studies on this topic. A study in Sydney, Australia, found that sex under the influence of drugs among people who inject drugs was associated with having a lower likelihood of being in drug treatment, having a higher number of sexual partners, sharing injection equipment with other people, being intoxicated when injecting, and being not sex workers Ross et al. The evidence of the association between drug use and sexual risk behaviors in HIV key populations in Cambodia has been well documented Coupland et al. However, no studies have examined risk factors associated with sex under the influence of drugs among PWUD. A recent study examined sexual risk behaviors among male and female adults who use drugs in Cambodia, but sex under the influence of drugs was not an outcome measure Ngor et al. Therefore, this study aims to fill this gap and contribute to the international literature by exploring the prevalence and associated factors of sex under the influence of drugs among PWUD in Cambodia. Our results will inform future policy of the prevention of sexual risk behaviors in this HIV key population. We excluded participants who reported that they did not have sexual intercourse and did not use any illicit drugs in the past three months. The survey was conducted between June and December in 12 provinces, where 21 operational districts with a high HIV and drug use burden were located. They referred to individuals who used any illegal injecting or non-injecting drugs in the last 12 months. Individuals eligible for the survey must be at least years-old, meet the survey definition of PWUD, be able to communicate in Khmer, and voluntarily provide written informed consent to participate in the study. The recruitment procedures followed four steps. First, four eligible seeds with an established social network of at least three PWUD in each study location were identified with assistance from non-governmental organizations working in the data collection sites. Second, a personal identification number was then assigned to each participant who had signed the consent form. Third, each seed was provided with three coupons for referring three other PWUD in their network to the study. Finally, the recruited participants were offered an opportunity to be a seed and refer other peers to the study using coupons provided by the study team. Two data collection teams were formed. Each team comprised one field supervisor, five interviewers, one lab technician, and one counselor. The teams were trained about data collection procedures, informed consent process, interview techniques, participants' confidentiality and privacy protection, and questionnaire administration practices. The teams were also required to review the study protocol and data collection tools. The team leaders also reviewed their team members' performance daily and addressed issues during the fieldwork. Before the interview, the counselor explained the potential risk and benefits of the study to the participants and obtained written informed consent from the participants. We adapted existing tools from our previous studies on HIV key populations in Cambodia to develop this survey questionnaire Sopheab et al. A workshop for the questionnaire validation was conducted with participation from representatives of communities and stakeholders working on HIV and harm reduction. The questionnaire was pretested to ensure that the contents were suited to the context, and the data collection teams were adequately able to smoothly conduct the data collection. We designed the questionnaire to collect sociodemographic information, including residence types rural or urban , sex, age, ethnicity, marital status, education, living arrangement, occupation, and income. The questionnaire also collected information on sexual behaviors, such as the number of sexual partners, frequency of condom use, having sex in exchange for money or goods, and having sex under the influence of drugs with any partner in the past three months. We categorized the number of sexual partners into three groups based on its distribution. The survey also collected information related to substance use behaviors, such as the type of drugs used, duration of drug use, experience in a drug rehabilitation center, and the size of the network of drug users they knew. We dichotomized methamphetamine and heroin use separately and grouped the duration of drug use based on its distribution. Similarly, we grouped the number of drug users that the participants knew into three groups based on its distribution. Individuals who had the sum score above the mean cut-off were considered to have high psychological distress. We built a multiple logistic regression model to identify factors associated with sex under the influence of drugs, following several steps. First, we grouped continuous variables based on their respective distributions. Next, bivariate analyses were conducted using the chi-square test to examine the association between sex under the influence of drugs and variables selected based on previous studies. The model included drug use duration instead of age because the two independent variables affected the outcome similarly and were correlated. We also performed sensitivity analyses to see whether results for men differed from those for women, as shown in the literature Calsyn et al. We removed all personal identifiers from the data collection documents. The study participants provided written informed consent before the data collection started. Table 1 shows the sociodemographic characteristics of the study participants. Of the total participants, The majority More than two-thirds More than half One in ten participants 9. Almost one in five Around one-third Table 2 shows that Half reported having sex with two or more partners About one-third A significantly higher proportion of the participants who reported having sex under the influence of drugs had their first sex before they turned years-old As shown in Table 2 , One-third Less than one in five Slightly less than half A significantly higher proportion of the participants who reported having sex under the influence of drugs in the past three months used methamphetamine Table 3 shows the results of the bivariate and multiple logistic regression analyses. The odds of having sex under the influence of drugs were significantly higher in participants living in urban areas AOR 2. The odds were also significantly higher in participants having two to three AOR 2. The odds of having sex under the influence of drugs were significantly higher in participants who reported having sex in exchange for money or goods AOR 1. Similarly, the odds of having sex under the influence of drugs were significantly higher among participants who had used drugs for more than three years relative to those who used drugs for less than one year AOR 1. We reran Tables 1 — 3 for male and female subgroups separately to examine whether these results differed from those in the overall sample See Tables S1, S2, S3, S4, S5, and S6 in the Supplementary Materials. Results in multivariable analyses were quite similar in men, but the results were moderately different in women from those in the overall sample. This study documented a high prevalence of sex under the influence of drugs among PWUD in Cambodia at The prevalence was lower than the This finding is unique to Cambodia since it departed from findings in the literature Scott-Sheldon et al. PWUD living in urban areas exhibited a higher probability of having sex under the influence of drugs than their rural peers. Urbanization could have facilitated this association. Evidence of the linkage between urbanization and increased drug availability and use has been documented Paykel et al. Our findings point to the need for an increase in community-based harm-reduction services for PWUD in urban areas. We found that sex under the influence of drugs was associated with the number of sex partners, consistent with the findings in previous studies. For instance, a study among people who inject drugs in Australia identified the number of sexual partners as a predictor of sex under the influence of drugs Ross et al. Similar results were found in men and women. This finding could be attributed to the number of PWUD whom the participants had known. In this study, the participants with a PWUD network of 10 or more were twice as likely to engage in sex under the influence of drugs. These results suggest that future interventions aiming to prevent sex under the influence of drugs, and HIV infection should devise a strategy to identify and target PWUD with multiple sexual partners and an extensive PWUD network. Sex in exchange for money or goods was associated with sex under the influence of drugs, consistent with findings in a study in Iran Kamel-Khodabandeh et al. Our subgroup analyses confirmed the association in men but not in women. This finding was surprising since close to half of women engaged in the entertainment sector in which transactional sex was more common Brody et al. We speculated that long-term drug use might have mediated the association among male participants as close to half of the men who had transactional sex had been using drugs for at least three years. Our finding highlights the need for interventions that target male long-term drug users to reduce the prevalence of sex under the influence and prevent HIV infections. Furthermore, methamphetamine use was associated with sex under the influence of drugs. Similar results were found in both men and women. The relationship between drug use, methamphetamine use in particular, and sexual risks in HIV key populations in Cambodia have also been reported Coupland et al. However, other types of drugs are also associated with sexual risk behaviors in other settings. For instance, McKeganey and Banard noted that some drugs such as temazepam made individuals too intoxicated to take sexual precautions, while Wachter et al. These findings suggest that the association between drug use and intoxicated sex is context-specific. Our study also found that participants who had used drugs for three or more years were more likely to report sex under the influence of drugs than those who had used drugs for one year or less. Similar findings were found in men but not in women. The association was likely mediated by drug use behaviors among men since methamphetamine use among men had a stronger association with sex under the influence than that among women. The drug use and sexual risk behavior nexus was also confirmed in a previous study in Cambodia Coupland et al. Last, we found that the participants with drug rehabilitation experience were more likely to have sex under the influence of drugs. A similar result was found in men but not in women. In this study, This finding points to the need for sexual risk education among male PWUD who had been to a drug rehabilitation center. This study has some limitations. First, causality cannot be drawn as this study was cross-sectional and did not account for temporality. Second, we might have either over or underestimated the prevalence of sex under the influence of drugs because we used a single self-reported question that may lead to social desirability bias. Participants, particularly women, may shy away from reporting the experiences. Third, our study was not an event analysis, which limited us from drawing temporal relationships between covariates and outcome of interest. Last, our results were likely driven by selection bias. Only areas with a heavy burden of HIV and PWUD population were targeted for the data collection, and a token was provided to participants as compensation for their time. This study was the first to document a high prevalence of sex under the influence of drugs among PWUD in Cambodia. Several risk factors of sex under the influence of drugs were identified. The results point to the need for integrating HIV and harm-reduction programs using innovative approaches to address the overlapping risks in this key population. The programs may be devised with motivational and skills training Calsyn, Cousins, et al. They should be specifically designed to address each identified risk factor to ameliorate the prevalence of sex under the influence of drugs, reducing the HIV incidence. They cannot be made available in the manuscript, the additional files, or a public repository. However, they can be accessed upon request from the Principal Investigator, Dr. Siyan Yi siyan doctor. Armstrong, G. Quality of life, depression, anxiety and suicidal ideation among men who inject drugs in Delhi, India. BMC Psychiatry, 13 1 , Article Google Scholar. Baseman, J. Sale of sex for drugs and drugs for sex: An economic context of sexual risk behavior for STDs. Sexually Transmitted Diseases , 26 8 , — Article PubMed Google Scholar. Brody, C. Childhood conditions, pathways to entertainment work and current practices of female entertainment workers in Cambodia: Baseline findings from the Mobile Link trial. Browne, D. Drug use and high-risk sexual behaviors among African American men who have sex with men and men who have sex with women. American Journal of Public Health, 99 6 , — Calsyn, D. Sex under the influence of drugs or alcohol: Common for men in substance abuse treatment and associated with high risk sexual behavior. American Journal on Addictions, 19 2 , — Reducing sex under the influence of drugs or alcohol for patients in substance abuse treatment. Addiction, 1 , — Coupland, H. Structural interventions and social suffering: Responding to amphetamine-type stimulant use among female entertainment and sex workers in Cambodia. International Journal on Drug Policy, 64 , 70— Ding, Y. Sexual risk behaviors among club drug users in Shanghai, China: Prevalence and correlates. AIDS and Behavior, 17 7 , — Fordham, G. Adolescent and youth reproductive health in Cambodia: Status, issues, policies, and programs. Goldberg, D. The detection of psychiatric illness by questionnaire: A technique for the identification and assessment of non-psychotic illness. Oxford University Press. Google Scholar. Transactional sex among noninjecting illicit drug users: Implications for HIV transmission. Scientific World Journal. Kamel-Khodabandeh, A. Sex under influence of drugs: A nationwide survey among Iranian female sex workers. Leigh, B. Alcohol, drugs, and condom use among drug offenders: An event-based analysis. Drug and Alcohol Dependence, 93 1 , 38— Substance use and risky sexual behavior for exposure to HIV: Issues in methodology, interpretation, and prevention. American Psychologist, 48 10 , — Mackesy-Amiti, M. Psychiatric correlates of injection risk behavior among young people who inject drugs. Psychology of Addictive Behaviors, 28 4 , — Mai, V. Factors influencing pre-marital sexual intercourse among unmarried young individuals in Cambodia. Makara Journal of Health Research, 23 3 , — Mburu, G. Prevalence and correlates of amphetamine-type stimulant use among transgender women in Cambodia. International Journal on Drug Policy, 74 , — McKeganey, N. AIDS, drugs, and sexual risk: Lives in the balance. Open University Press. Newville, H. Temporal relationship of sex risk behaviors and substance use severity among men in substance use treatment. Journal of Sex Research, 55 8 , — Ngor, C. Factors associated with sexual risk behaviors among people who use drugs in communities in Cambodia. Asia-Pacific Journal of Public Health, 31 4 , — Page, K. Cluster randomized stepped-wedge trial of a multi-level HIV prevention intervention to decrease amphetamine-type stimulants and sexual risk in Cambodian female entertainment and sex workers. Drug and Alcohol Dependence, , 21— Paykel, E. Psychological Medicine, 30 2 , — Rawson, R. Drugs and sexual effects: Role of drug type and gender. Journal of Substance Abuse Treatment, 22 2 , — Ritchie, H. Our World in Data. Ross, M. Predictors of intoxicated sex in injecting drug users. Journal of Addictive Diseases, 13 2 , 69— Scott-Sheldon, L. Alcohol consumption, drug use, and condom use among STD clinic patients. Journal of Studies on Alcohol and Drugs , 70 5 , — Smith, L. Making and communicating decisions about sexual consent during drug-involved sex: A thematic synthesis. Journal of Sex Research. Sopheab, H. BMC Infectious Diseases, 18 , Spauwen, L. Drug use, sexual risk behaviour and sexually transmitted infections among swingers: A cross-sectional study in The Netherlands. Sexually Transmitted Infections, 91 1 , 31— Sundquist, K. Urbanization and hospital admission rates for alcohol and drug abuse: A follow-up study of 4. Addiction, 99 10 , — Suohu, K. Understanding the association between injecting and sexual risk behaviors of injecting drug users in Manipur and Nagaland India. Harm Reduction Journal, 9 1 , Tuot, S. Prevalence and correlates of HIV infection among people who use drugs in Cambodia: A cross-sectional survey using respondent driven sampling method. BMC Infectious Diseases. Sexual and reproductive health of adolescents and youth in Cambodia: Analysis of — Cambodia Demographic and Health Survey Data. Wachter, R. Journal of the American Medical Association , 22 , — Yi, S. Prevalence of and risk factors for hepatitis C virus antibody among people who inject drugs in Cambodia: A national biological and behavioral survey. Harm Reduction Journal, 16 1 , Syphilis infection among people who use and inject drugs in Cambodia: A cross-sectional study using the respondent-driven sampling method. Mental health among men who have sex with men in Cambodia: Implications for integration of mental health services within HIV programmes. International Journal for Equity in Health, , Zhao, Q. Sexual risk behaviours and correlates of condom use with casual sex partners among drug users in Jiangsu, China. Drugs: Education, Prevention and Policy, 26 5 , — Zule, W. Journal of Rural Health, 23 , 73— Download references. Special thanks are also extended to all data collection teams, community-based organizations, local authorities, and the participants for their excellent contribution to this study. You can also search for this author in PubMed Google Scholar. All authors contributed to the conceptualization of the research questions, interpretation of the results, and manuscript writing. All authors read and approved the final manuscript. Correspondence to Siyan Yi. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. Reprints and permissions. Saing, C. Arch Sex Behav 51 , — Download citation. Received : 17 December Revised : 01 August Accepted : 20 November Published : 22 February Issue Date : April Anyone you share the following link with will be able to read this content:. Sorry, a shareable link is not currently available for this article. Provided by the Springer Nature SharedIt content-sharing initiative. Archives of Sexual Behavior Aims and scope Submit manuscript. Download PDF. Abstract Studies in drug use settings rarely use sex under the influence of drugs as an indicator of sexual risk behaviors. Selling sex in the context of substance use: social and structural drivers of transactional sex among men who use opioids in Maryland Article Open access 15 October Use our pre-submission checklist Avoid common mistakes on your manuscript. Introduction People who use drugs PWUD , including people who inject drugs, are highly exposed to sexual risk behaviors, such as sex under the influence of drugs. Measures We adapted existing tools from our previous studies on HIV key populations in Cambodia to develop this survey questionnaire Sopheab et al. Results Sociodemographic Characteristics Table 1 shows the sociodemographic characteristics of the study participants. Table 1 Sociodemographic characteristics of people who use drugs with and without sex under the influence of drugs in the past 3 months Full size table. Table 2 Sexual behaviors, substance use, and psychological distress among people who use drugs with and without sex under the influence of drugs in the past 3 months Full size table. Table 3 Risk factors associated with sex under the influence of drugs in the past 3 months among people who use drugs in bivariate and multiple logistic regression analyses Full size table. Conclusions This study was the first to document a high prevalence of sex under the influence of drugs among PWUD in Cambodia. References Armstrong, G. Article Google Scholar Baseman, J. Article Google Scholar Mai, V. Google Scholar Newville, H. Article Google Scholar Spauwen, L. Article Google Scholar Yi, S. Article Google Scholar Download references. View author publications. Ethics declarations Conflict of interest The authors declare that they have no conflict of interests. Informed Consent Written informed consent was obtained from each study participant. Additional information Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Supplementary Information. About this article. Cite this article Saing, C. Copy to clipboard. Search Search by keyword or author Search. Navigation Find a journal Publish with us Track your research.

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Buying Heroin Guimaraes

Official websites use. Share sensitive information only on official, secure websites. Corresponding author. E-mail address: guilherme. Moreira de Barros. The work cannot be changed in any way or used commercially without permission from the journal. Methadone administration for outpatient was noninferior to morphine as analgesic on chronic pain. In addition, it was associated with lesser side effects. Chronic pain causes disability and is prevalent in the general population. Opioids are a part of a multimodal strategy for pain management. Methadone, a cheap and long-acting synthetic opioid, may represent an option for those who have limited access to the aforementioned class of analgesics. We aimed to provide a real-world evidence for the analgesic use of methadone, compared with morphine. We conducted a noninferiority, retrospective observational single center study of patients with chronic pain, managed with either methadone or morphine at an outpatient specialized clinic. We extracted data from the electronic health records of patients who underwent an active treatment between August and January and were examined for at least 2 consecutive medical visits, after the administration of one of the aforementioned drugs. Data were analyzed using a generalized additive model with random-effects mixed linear method to account for the individual-related, time-related, and drug-related variations. The numeric verbal scale 0—10 was used to assess the pain severity. From the database of patients, we included patients methadone and 87 morphine. In an unadjusted analysis, methadone was superior to morphine, and the mean worst pain was 0. Moreover, methadone was superior to morphine in the adjusted analysis, with the worst pain mean being 1. This provided evidence for the noninferiority of methadone than morphine. Chronic pain is a common cause of severe disability. Approximately 1 in every 5 American adults, or 30 million people, experience chronic pain, thereby representing a substantial loss to the economy. The use of opioid analgesics is ubiquitous in cancer pain. However, there are conflicting reports for chronic noncancer pain. Some studies have reported on good pain relief with the long-term use of opioids, occasionally with functional improvement. Considering the commonly selected samples in multidisciplinary pain control programs, other studies conclude that chronic opioid therapy exacerbates psychological distress, impairs cognition, and worsens the outcomes. Finally, the use of opioid analgesics has gained attention in lay media as well as in scientific publications. This can be attributed to the opioid crisis in several countries and, in particular, in the United States. Nonetheless, we cannot underestimate the proportion of people worldwide who still do not have adequate access to the aforementioned essential analgesics. Methadone is a long-acting synthetic and easily manufactured opioid, first developed during World War II. It is commonly considered a cornerstone in the treatment of opioid addicts. However, it is being increasingly used for its analgesic properties. Therefore, its use may be particularly appealing in low-income populations or developing countries, such as Africa and Latin America. The aforementioned special features enable methadone to modulate pain stimuli propagation to reduce the development of hyperalgesia and opioid tolerance. However, prescribing methadone analgesic is challenging owing to the wide interindividual variability in its pharmacokinetics. This characteristic makes it difficult to predict the relationship between the dose, plasma concentrations, and pharmacologic effects. It is classified as a strong opioid analgesic, similar to methadone, used for the management of acute and chronic pain of moderate to severe intensity. Few studies have compared methadone and morphine for the management of chronic pain in patients treated at an outpatient specialized clinic. In addition, no study has compared these strong opioids in a real-world clinical setting. Studies with real-world data RWD include information from prospective or retrospective observational studies. Unlike controlled trials, patients in the aforementioned studies are treated according to the local clinical characteristics and preferences. In addition, evidences extracted from the RWD represent a situation closer to the procedures adopted in clinical practice. Thus, they comprise interferences that are often not a part of controlled and randomized studies, such as the existence of comorbidities, concomitant treatments, lack of data, discontinuities, and low adherence. We aimed to provide real-world evidence for the analgesic use of methadone, compared with morphine. Our primary objective was to evaluate pain improvement in outpatients diagnosed with chronic pain of various etiologies who were administered morphine or methadone. We also intended to evaluate the incidence of analgesic-associated adverse events. We hypothesized that analgesic effects of methadone in a real-life setting are not inferior to that of morphine. Our study was approved by the institution's ethical committee in human research, which waived the need for patient's informed consent because it was a retrospective study and all data were unidentified. We conducted a noninferiority, retrospective observational single center study comprising patients with chronic pain, managed with methadone or morphine at an outpatient specialized Pain Management and Palliative Care Unit of the Teaching Hospital of Botucatu Medical School—UNESP, Brazil. The report is in accordance to the Strengthening the Reporting of Observational Studies in Epidemiology statement. We obtained the electronic health records from October to March , and included those who underwent active treatment between August and January , during which the records were documented in the institution. These records comprised a specific pain form that was searched during data collection. We excluded patients with incomplete medical records. Patients who were administered analgesic interventions, unable to inform their pain score, or using other opioids were excluded. All medical visits were documented for analysis purposes. Only those patients who adhered to the prescribed oral doses of methadone or morphine, according to the need for treatment of each patient and clinical condition, were included. Moreover, their use is extremely flexible, depending on the individualized demand of the patient. Other adjuvant analgesics, including paracetamol or tricyclic antidepressants, could be simultaneously used. Laxatives were routinely prescribed at libidum to all participants with a prescribed opioid at the clinic. All medications in use were recorded. Patients who clearly did not adhere to treatment were not included in the study. We analyzed data from the worst pain experienced by the patients. Secondary effectiveness outcomes included the performance status measured by the Karnofsky Performance Status and the occurrence of side effects registered in the medical records. The patients were categorized by their sex, age, and pain origin classification nociceptive, neuropathic, mixed, and nociplastic pain in accordance to the diagnosis. Baseline characteristics of the study population and safety were reported using descriptive statistics. We conducted the Fisher exact test, t test, or Wilcoxon—Mann—Whitney when appropriate to test the hypothesis of differences between the groups. To compare the effectiveness of methadone and morphine in pain management, we used a noninferiority hypothesis. Data collected after days were excluded. For graphical reasons, we converted the dates to bin intervals of 40 days. We plotted both error plots and predicted the continuous data using locally weighted scatterplot smoothing. We analyzed the longitudinal data using a generalized additive model GAM with integrated smoothness estimation using the function GAM from the mgcv package for R and the random-effects mixed linear method read the Statistical Analysis Code for more details to account for the individual-related, time-related, and drug-related variations. A secondary analysis using data obtained after days of inclusion was performed to exclude the possible effects of outliers in the third time bin 79— days. The database included patients, of whom were administered methadone or morphine. They had been registered for at least 2 consecutive medical appointments, with an interval of up to 12 months, which reflected the time of continuous use of each analgesic. We included only those patients who had consumed the medications as directed by the assistant physician. Of the selected patients, met the inclusion criteria. Methadone or morphine was used by and 87 patients, respectively Fig. The mean age of patients consuming methadone and morphine was Most patients were female Nonetheless, the distribution was more equal for those consuming morphine. Table 1 summarizes the patient anthropometrics and pain classifications. Patient anthropometrics, median of opioid consumption, and pain origin, in accordance to the diagnosis. Mean during the entire follow-up period standard deviation , value expressed in mg. In our adjusted analysis, methadone was superior to morphine, and the worst pain mean was 1. However, we noticed a high effect in the third time bin. Best pain scores at the first 40 days bin were 4. We then excluded data from the first days to determine whether methadone performed worse than morphine, as a worst-case scenario. Methadone predicted a lower mean of worst pain even in the second analysis Table 3. Nonetheless, the difference was statistically insignificant. Numeric verbal scale NVS scores 0—10 scores for worst pain in patients consuming methadone or morphine during the follow-up. Generalized additive model with integrated smoothness estimation. There were few reports in the medical records on the occurrence of opioid use—related adverse events. Therefore, we could not conduct statistical tests for comparing between the 2 groups. Nausea was the most frequently registered side effect Table 4. During the visits, the average of the Karnofsky scale was stable, oscillating between 75 and 82 in the groups data not shown. The P value was 0. Evaluating the difference observed in the Karnofsky Scale: during the first medical appointment and after the introduction of studied analgesics. Although methadone doses were extremely stable during the follow-up, morphine doses were more variable and even decreased at the end of a year of follow-up Table 1 and Fig. Few studies have compared between methadone and morphine for the treatment of opioid use disorder 24 as well in the perioperative setting. Moreover, none of them focused on a real-life setting. Of the total health records evaluated, only patients 7. This low sample size may reflect the difficulty to obtain RWD. This is because numerous clinical records are incomplete and several important information may be missing. We only considered reliable data obtained from the health records for analysis, thus ensuring the patients presented adequate compliance to the prescribed medicines. Moreover, we adopted a judicious inclusion criteria that sought to remove interferences from other pharmacological or nonpharmacological treatments that could alter the pain pattern. The results and conclusions of studies including RWD currently represent strong evidences. Few years ago, the U. Food and Drug Administration FDA released a draft guidance on the use of real-world evidence to support regulatory decision making for medical devices. The FDA guidance defines RWD as data collected from different sources, including retrospective studies and electronic health records. The mean age of our selected patients was quite similar to the age of individuals included in a population-based chronic pain survey, conducted at the city where the pain clinic was located. While the mean age of the included patients was Chronic pain was more prevalent in women This may be attributed to the characteristics of experienced pain, particularly neuropathic pain. The prevalence of neuropathic pain is higher in women and increases with age. Morphine and methadone were the only strong opioids free of charge at the above-mentioned government-sponsored pain clinic. Nociceptive pain was more prevalent in patients who received morphine. By contrast, mixed and nociplastic pain were more prevalent among methadone users. Despite the equal distribution of patients with neuropathic pain in both groups, the proportion was slightly higher among methadone users. Our findings are similar to Latina et al. In cancer pain, opiophobia and morphine avoidance are less common. Furthermore, as opioid use disorder is not a prevalent problem in Brazil, 30 there is no social stigma associated with methadone because it is not used in the treatment of heroin addicts, unlike other countries. Our primary hypothesis was that methadone was not inferior to morphine during chronic pain management. Interestingly, methadone was superior to its comparator analgesic, however, without any clinical relevance. A reduction of approximately 2 points in the pain score is necessary to represent a clinically relevant difference. Methadone presents several advantages over morphine in the treatment of cancer pain. However, a consensus has not yet been achieved. Methadone usage has not achieved a consensus even in chronic noncancer pain. Moreover, it raises concerns, particularly after the development of recreational opioid crises in some countries. We did not record any life-threatening events, including respiratory depression because of overdose or opioid addiction. Raja et al. Opioid side effects in patients with chronic noncancer pain may increase their morbidity and mortality, affect the quality of life, and lead to the discontinuation of chronic opioid therapy. Adverse events occur at all dose ranges, despite an increase in their frequency with regular opioid use, higher doses, long-term therapy, polypharmacy, and decreased renal or hepatic function. Methadone doses were much more stable over time than morphine, which may represent superiority over morphine. Henry et al. The overall dose of both opioids in our study was low and might have influenced the low incidence of side effects, including the life-threatening ones. Moreover, Trofimovitch et al. The mean methadone dose registered in our study was Physicians should consider the performance status while prescribing opioids for chronic pain. Poor performance status in patients with cancer is often associated with higher symptom burden, predominantly pain, which may demand higher opioid use. This can be attributed to the lack of difference in the performance status between methadone and morphine, as measured by the Karnofsky score. There are limited data supporting the long-term use of opioids for noncancer pain relief. Moreover, we do not advise the undiscerning prescription of opioids. However, we believe that patients with chronic noncancer pain, who are likely to benefit from potent opioids, should not be prevented from obtaining this treatment. Therefore, careful selection of patients, meticulous prescriptions, and monitoring of protocols should be enforced. Guidelines on long-term opioid therapy recommend a single physician to conduct the medication management. All patients must undergo a clinical risk evaluation. The treatment agreements must be signed, and physicians must perform periodic monitoring, urine drug screening, and the documentation of treatment in the medical records. Despite ensuring the precise documentation of all data available in the health records, the study had few limitations. Our findings were observational in nature, and we failed to establish a causation. Methadone is still considered an analgesic that should only be prescribed by physicians with an experience and expertise in its use. Side effects rarely occurred, and there were no reports of life-threatening events. Methadone users presented a more stable state during the investigation. The authors are grateful to Prof. Fernanda Bono Fukushima for helping with the concept of the study design. The principal investigator G. Moreira de Barros and the co-authors F. Domingues, M. Gayoso, A. Lopes, and G. Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article. As a library, NLM provides access to scientific literature. Pain Rep. Find articles by Guilherme Antonio Moreira de Barros. Find articles by Ricardo Baradelli. Find articles by Debora Garcia Rodrigues. Find articles by Odaly Toffoletto. Find articles by Flavia Seullner Domingues. Find articles by Maisa Vitoria Gayoso. Find articles by Alexandre Lopes. Find articles by Jorge Barros Afiune. Published by Wolters Kluwer Health, Inc. Open in a new tab. Effect Estimate P Intercept 8. Mixed-effects model summary to predict worst pain in the subset after days. Effect Estimate P Intercept 9. Similar articles. Add to Collections. Create a new collection. 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Buying Heroin Guimaraes