A hospital-based multi-centric observational study to explore the prevalence and correlates of non-medical use and dependence of pregabalin among the patients with substance use disorder in Punjab & Chandigarh

Abstract

Background and aim

Pregabalin (a Gabapentinoid) has been shown to have potential for non-medical use. We aimed at exploring the prevalence and clinical correlates of non-medical use of pregabalin and dependence in patients seeking treatment for substance use disorders (SUDs).

Materials and methods

Patients with ICD-10 diagnosis for various SUDs, in the age range of 18–70 years who consented for participation in this study were evaluated for non-medical use and dependence of pregabalin across three different regions of Punjab and the union territory of Chandigarh. ICD-10 criteria for a dependence syndrome (three or more criteria) were used for defining dependence on pregabalin.

Results

Out of a total 974 patients enrolled in this study, 44.6% of study participants were using pregabalin and 24.8% fulfilled ICD-10 criteria for a dependence syndrome. Compared to study subjects having non-medical use of pregabalin, a significant number of persons using pregabalin in dependent fashion consumed pregabalin with a frequency of more than 3 times/day (p < 0.001), with daily consumption of pregabalin in doses more than 1200 mg/day (p < 0.001) and suffered from seizures (p < 0.001). Significantly high rates of pregabalin non-medical use and dependence were observed in Sikh patients (p < 0.01), living in rural areas (p < 0.01), who were unmarried/single (p < 0.001), educated more than 10 years (p < 0.01), and with an opioid use disorder (p < 0.001). Pregabalin non-medical use and dependence were also significantly higher in younger patients (p < 0.001), with a younger age of onset of substance use disorder (p = 0.014) and with shorter duration of substance use (p < 0.001). The odds of use of pregabalin were higher in patients with opioid use disorder (aOR = 5.3, 95% CI 3.5–7.9; p < 0.001) in comparison to those with alcohol use disorder.

Conclusion

These high estimates for non-medical use and dependence of pregabalin in our study are an early indication of rising problem of pregabalin use amongst the patients with substance use disorders. We draw attention of the healthcare providers and policy makers in formulation of strategies to screen for pregabalin non-medical use and dependence, formulate treatment strategies and devise policy changes to address diversion of pregabalin in view of its non-medical use potential.

Introduction

The gabapentinoid drugs namely pregabalin and gabapentin are approved for many long-term conditions like epilepsy, post-herpetic neuralgia, neuropathic pain, and diabetic neuropathy [1]. Further, pregabalin has also been used for management of generalized anxiety disorder and fibromyalgia. Gabapentinoids are structural analogue of ɣ-aminobutyric acid (GABA), though these do not act on GABA receptors. Further, these are selective ligands for the alpha-2-delta subunit of voltage-gated calcium channels (VGCC) and have been demonstrated to restrain stimulus-dependent synaptic transmitter release, mainly the excitatory transmitters glutamate and norepinephrine [2]. Due to their mild dose related increase in extra-cellular GABA levels, these are supposed to have euphoric effect [3, 4]. Concerns regarding the possibility of high-risk usage, and off-label use are brought on by their growing use. Subtherapeutic prescription as well as substantial off-label usage have also been reported. The non-medical use potential of pregabalin has been tested in-vitro as well as in-vivo. However, various animal studies produced conflicting results, some showing no association with rewarding effect while others mentioning that it led to dose-related rewarding effects [5–7].

The National Institute on Drug Abuse (NIDA) defines non-medical use as “use of a medication without a prescription, in a way other than as prescribed, or for the experience or feelings elicited” [8]. The terms prescription drug abuse or misuse and non-medical use are often used interchangeably, but we will be using the term non-medical use hereafter to avoid any stigmatizing connotations. International Classification of Diseases 10th edition provides diagnostic criteria for dependence syndrome characterized by three of more of the following namely a strong desire or compulsion to take the drug, difficulty controlling the substance taking behavior, a physiological withdrawal state, development of tolerance for the effects of drug, progressive neglect of alternative pleasures or interests because of substance use and persistent use despite clear evidence of harmful consequences [9].

The data for the non-medical use of gabepentinoids is available in form of post-marketing pharmacovigilance studies, analysis of the prescriptions, and clinical toxicological studies. Some of the earliest post-marketing pharmacovigilance surveys conducted in the US and Europe have shown that the range of non-medical use of gabapentinoids was 1.5%-26.1%, and pregabalin was more often used in comparison to gabapentin. Further, in some of the studies wherein a control drug was also assessed (such as duloxetine, amitriptyline and clonazepam), the prevalence of non-medical use of gabapentinoids was less [10–13].

Previous studies have shown non-medical use of pregabalin by young patients to seek “high/euphoria”, consumption up to 300-4200 mg of pregabalin/gabapentin per day, and withdrawal symptoms such as aches and pains, anxiety, lethargy, and avoidance of social interaction [14–16]. Evidence for non-medical use of pregabalin in Indian context is available in form of case reports/series and a recent retrospective analysis of admission case records [17–21]. The severity of non-medical use of pregabalin may be gauged from the fact that seizure of large quantities of pregabalin has occurred in various districts of Punjab, India and that some of the district administrations have even prohibited the sale of pregabalin 300 mg without a prescription (For e.g. vide Office Order No:2021/FS/FK-2- 25645-25711, Dated: 12 October 2021).

With this background, we undertook this multicentric hospital based observational study across different regions of Punjab and the union territory of Chandigarh to evaluate the prevalence of non-medical use of pregabalin among the patients with substance use disorders who were consulting for treatment at any of the participating study sites. We hypothesized that patients with non-medical use and dependence on pregabalin would show distinctive substance use profile as well as socio-demographic attributes.

Materials and methods

Study design

A cross‑sectional analytical design was used for this study. It was a multi-centric study in which study participants from multiple tertiary care centers located in three different regions of Punjab and the Union Territory of Chandigarh were enrolled. The study was carried out from September 2023 to August 2024. All the study participants were enrolled after obtaining written informed consent. The study was approved by the ethics committee of all the participating sites (vide IEC/AIIMS/BTI/396, GMCH/IEC/2023/1114R, GMC/IEC23/NB/139, No. Trg. 9(310)2023/35277, and DMS/SPS-I/2023/64). The patients who attended the outpatient, as well as inpatient departments of the participating centres across Punjab & Chandigarh for treatment of substance use disorders were approached for participation in this study. The inclusion criteria were patients diagnosed with ICD-10 diagnostic criteria for substance use disorders, between age ranges of 18–70 years, of either gender and with adequate cognitive functions to perform the interview, and provision of written informed consent to participate in this study. A diagnosis of dependence syndrome on pregabalin was arrived at using the ICD-10 criteria for substance use disorder i.e. fulfilling three or more criteria while those not fulfilling these criteria were put in category of pregabalin non-medical use. Patients who were intoxicated or currently in withdrawal of a substance were only enrolled after their detoxification phase was over. Patients with intellectual disability or dementia, or those who refused to give a written informed consent and subjects who were medically unstable for interview were excluded. We used ICD-10 diagnostic categories as none of the participating sites have shifted to ICD-11 codes for the purpose of clinical records and insurance.

A sample size of 189 was calculated for each site using the single population proportion formula after considering the overall non-medical use of gabapentinoids in patients with history of substance use to be around 9% [22], with a 95% confidence interval and a margin of error of 5%, and design effect of 1.5.

The study participants provided their socio-demographic details which were recorded using a predesigned proforma. Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST B Hindi version 3.0; World Health Organization, 2002)- ASSIST, an 8-item questionnaire, was utilized to elicit hazardous and harmful substance use in addition to the clinical evaluation [23]. This tool has been found to be valid and reliable in field testing [24].

Psychiatric diagnosis was established as per the International Classification Diseases, Tenth Revision (ICD-10; WHO, 1993) diagnostic criteria for substance use disorders as well as co-morbid psychiatric disorders [9]. The diagnosis of substance use disorders and psychiatric conditions were clinically established by a trained psychiatrist. Physical morbidities were assessed using a separate sheet and a semi-structured proforma (based on the clinical features from previous studies) was utilized to enquire about the non-medical use of pregabalin, duration of non-medical use, source of procurement and so on. All the study tools were converted to a google form which was pre-tested in a set of 50 patients with the purpose to revise the items and to check the feasibility to carry out the data acquisition using the google form. However, a written informed consent was obtained on paper from each of the consenting participant at various sites where the study was carried and the records were preserved as per mandate of respective institutional ethics committee.

Statistical analysis

SPSS 29.0 for Windows/Mac (IBM Software, Chicago) was utilized for performing statistical analysis. All the categorical values are presented as frequencies while continuous variables as means with standard deviations. Pearson’s chi-square test and student t-test were used to elicit the clinical correlates of pregabalin non-medical use and dependence in study subjects. Binomial regression analysis was done to evaluate the predictors of pregabalin non-medical use/dependence. The level of statistical significance was set at p-value less than or equal to 0.05. Missing data were handled using the available case analysis technique to retain maximum data for each analysis, leveraging partial information from cases with missing values.

Results

Socio-demographic and clinical characteristics of the study participants

Of the 1002 total responses recorded across the study centers, 974 valid responses were included in the analysis. An equal number of study participants were included from all the study sites namely Bathinda, Chandigarh, Amritsar, and Patiala except Ludhiana (Fig. 1). The selection of these sites was based on the premise that the tertiary care hospitals located in Bathinda, Patiala, Chandigarh and Ludhiana cater to the population of Malwa region of Punjab, while Amritsar and Ludhiana cater to Majha and Doaba region of Punjab. The socio-demographic profile of study participants included in the analysis is provided in Table 1. The socio-demography of the study participants can be compared with the 2011 National Census of India which showed a total population of 27.7 million making it the 16th largest stated of India. The population comprises of people of various faiths predominantly Sikhs (57.69%) followed by Hindus (38.49%), Muslims (1.93%) and Christians (1.26%). Punjab is largely an agrarian state with 62.5% residing in rural areas and 37.5% in urban localities with a literacy rate of 75.84%.

Fig. 1.

Visual map showing data intake from various regions of Punjab

Table 1.

Socio-demographic profile of the study participants & clinical correlates of pregabalin non-medical use and dependence

	Pregabalin No use (N/%)	Pregabalin non-medical use (N/%)	Pregabalin Dependence (N/%)	Total Sample (N/%)	p-value
Total	539(55.3)	193(19.8)	242(24.8)	974(100)
Age (in years)*	38.3(12.04)	30(8.05)	30 (7.84)	34.5(11.18)	< 0.001
Gender of the patient					0.362
Male	529(55.3)	188(19.6)	240(25.1)	957(98.2)
Female	10(58.8)	5(29.4)	2(11.8)	17(1.7)
Preferred Religion					0.004
Sikhism	327(51.7)	130(20.5)	176(27.8)	633(65.0)
Non-Sikhism	212(62.2)	63(18.5)	66(19.4)	341(35.0)
Residence					0.017
Urban	222(61.2)	65(17.9)	76(20.9)	363(37.3)
Rural	317(51.9)	128(20.9)	166(27.2)	611(62.7)
Family Type					0.061
Nuclear	302(54.7)	99(17.9)	151(27.4)	552(56.7)
Extended/ Joint	237(56.2)	94(22.3)	91(21.6)	422(43.3)
Marital Status					< 0.001
In-unison	380(63.4)	94(15.7)	125(20.9)	599(61.5)
Single	159(42.4)	99(26.4)	117(31.2)	375(38.5)
Occupation					0.224
Employed	371(53.6)	144(20.8)	177(25.6)	692(71.1)
Unemployed	168(59.6)	49(17.4)	65(23)	282(28.9)
Education					0.016
Less than 10 years	192(49.9)	82(21.3)	111(28.8)	385(39.5)
More than 10 years	347(58.9)	111(18.8)	131(22.2)	589(60.5)
Family Income (monthly)					0.318
Less than 10,000 INR	174(58.2)	51(17.1)	74(24.7)	299(30.7)
More than 10,000 INR	365(54.1)	142(21)	168(24.9)	675(69.3)
Primary SUD diagnosis Category					< 0.001
Alcohol Use Disorder (AUD)	208(84.6)	21(8.5)	17(6.9)	246(25.3)
Opioid Use Disorder (OUD)	284(43)	167(25.3)	209(31.7)	660(67.8)
Others	47(69.1)	5(7.4)	16(23.5)	68(6.9)
Age at onset of substance use*	25.1(7.86)	22.3(8.20)	21.6(6.62)	24(13.1)	< 0.001
Total months of duration of substance use*	136(113)	85(64)	95(74)	115(99.0)	< 0.001

*depicted as mean (SD)

Most of the study participants included male patients (98.3%), with a mean age of 34.5 (SD = 11.18) years. Nearly two third of the participants were affiliated to Sikhism (65%) while nearly one third followed Hinduism (32.2%) and the rest were Muslims (1.9%) and Christians (0.9%). Most of the study participants resided in the rural areas (62.7%). A little more than half lived in nuclear families (56.7%), nearly two-thirds were married (61.5%), had an education of more than 10 years (60.5%), were self-/employed (71%), and earned more than 10,000 Indian National Rupees per month (69.3%). Slightly more than one-third of the study participants suffered from one or more medical comorbidities (N = 355; 36.4%). The majority of these included hepatological conditions (38%, such as chronic liver disease, hepatitis, etc.), followed by cardiovascular diseases (17.5%; predominantly hypertension), neurological conditions (10.7%; epilepsy, migraine, etc.) and endocrinological disorders (9.6%; such as diabetes mellitus and hypothyroidism).

The mean age at initiation/onset of substance use was 24 (Range- 8 years to 65 years), and the total duration of months of any substance use was 115 months (Range- 1 month to 600 months). The predominant/primary substance use disorder was opioid use disorders (67.8%), followed by alcohol use disorders (25.3%). Twelve patients only used pregabalin as their primary drug of non-medical use. The second most common substance use disorder was tobacco use disorder, seen in nearly half of the study subjects (49.8%). It was also the most frequent substance use disorder at the 3rd and 4th rank in nearly two-thirds of the study participants (data not tabulated).

Pattern and clinical correlates of pregabalin non-medical use and dependence

About 435 (44.6%) of the study participants reported non-medical use of pregabalin, while none used gabapentin. Further, using the ICD-10 criteria for dependence, nearly one fourth (n = 242; 22.8%) of the study participants met criteria for a dependence syndrome while 193 (19.8%) used pregabalin in a non-dependent fashion labeled non-medical use hereon (Table 1).

The purpose of using pregabalin was to seek relaxation (n = 72; 16.8%), relief from pain (n = 52; 12.1%), get euphoria/high (n = 40; 9.3%), enhance the effect of other substances of use (n = 14; 3.3%), induce sleep (n = 13; 3%), relief from anxiety (n = 7; 1.6%), or a combination of these (n = 201; 46.8%) (Fig. 2). Some even reported the non-availability of heroin or insufficient money to buy their primary substance of use (n = 30; 6.9%) as the reason for using pregabalin. Most of them (n = 267; 61.4%) were introduced to pregabalin by their friends and procured it from a licensed chemist without a legible prescription (n = 319; 73.5%). About two-thirds of participants consumed pregabalin at a frequency of once or twice a day (n = 259; 60.1%), and in the dose range of 300 to 2400 mg daily (n = 277; 63.6%). Very high doses of pregabalin, i.e., beyond 2400 mg per day, were reported in about 12% (n = 52) of participants. About one third (n = 143; 34.45%) participants used one or more forms of opioids (mainly heroin) as the common drug of use with pregabalin. A history of an epileptic seizure consequent to non-medical use/dependence of pregabalin was reported in 34 (7.8%) participants. Nonetheless, 70.8% of participants were aware that the sale of pregabalin was not allowed without a legible prescription (data not tabulated).

Fig. 2.

Purpose of pregabalin non-medical use among study participants

Further comparisons between the patients with pregabalin non-medical use and dependence showed that a significant number of patients fulfilling ICD-10 criteria for a dependence syndrome consumed pregabalin in greater frequency of > 3 times/day (79.87% vs. 20.12%; p < 0.001), daily consumption of pregabalin in doses > 1200 mg/day (83.15% vs. 16.85%; p < 0.001), and suffered from seizures (88.23% vs. 11.76%; p < 0.001).

Table 1 also depicts the bivariate analysis done to ascertain the association between independent variables (socio-demographic and clinical characteristics) and pregabalin non-medical use and dependence. Pregabalin non-medical use and dependence was significantly associated (p-value < 0.05) with religion, place of residence, marital status, years of education, category of primary substance use disorder, mean age, duration of substance use (in months), and age at initiation of substance use (in years).

Further, the significant associations were additionally analysed using a bivariate logistic regression model in which use of pregabalin was entered as dependent variable.

The multivariable logistic regression model (Table 2) demonstrated adequate fit and calibration (Nagelkerke R² = 0.34; Hosmer–Lemeshow p = 0.59). In unadjusted analyses, increasing age was associated with lower odds of pregabalin use (OR = 0.90, 95% CI 0.90–0.90; p < 0.001). Gender was not significantly associated with pregabalin use. Participants identifying with Sikhism had higher odds of pregabalin use compared with non-Sikh participants (OR = 1.5, 95% CI 1.2–2.0; p = 0.002). Rural residence was associated with lower odds of pregabalin use compared with urban residence (OR = 0.7, 95% CI 0.5–0.9; p = 0.005). Employment status showed a non-significant protective association in unadjusted analysis (OR = 0.8, 95% CI 0.6–1.0; p = 0.090). Single marital status and shorter duration of education were associated with higher odds of pregabalin use in unadjusted models, whereas family structure and monthly family income were not significantly associated.

Table 2.

Binary logistic regression analysis to explore factors associated with pregabalin non-medical use and dependence

	Unadjusted Odds ratio (95% CI)	P-value	Adjusted Odds ratio (95% CI)	P-value
Age (in years)	0.9 (0.9–0.9)	< 0.001	0.9(0.9–0.9)	< 0.001
Gender of the patient
Female	1
Male	1.2 (0.4–3.1)	0.771	0.9(0.3-3)	0.898
Preferred Religion
Non-Sikhism	1
Sikhism	1.5 (1.2-2.0)	0.002	1.5(1.1–2.1)	0.014
Residence
Urban	1
Rural	0.7 (0.5–0.9)	0.005	0.7(0.5–0.9)	0.014
Occupation
Unemployed	1
Employed	0.8 (0.6-1.0)	0.090	0.5(0.3–0.7)	< 0.001
Family
Extended/ Joint	1
Nuclear	1.1 (0.8–1.4)	0.652	1.3(0.9–1.7)	0.140
Marital Status
In unison	1
Single	2.4 (1.8–3.1)	< 0.001	1.2(0.9–1.7)	0.265
Education (in years)
Less than 10 years	1
More than 10 years	0.7 (0.5–0.9)	0.006	0.8(0.6-1)	0.077
Family Income (monthly)
Less than 10,000 INR	1
More than 10000INR	1.2 (0.9–1.5)	0.233	1.1(0.8–1.5)	0.691
Primary SUD diagnosis Category
AUD	1		(-)	< 0.001
OUD	7.2 (4.9–10.6)	< 0.001	5.3(3.5–7.9)	< 0.001
Others	2.4 (1.3–4.5)	0.005	1.8(0.9–3.6)	0.081
Total months of duration of substance use	0.9 (0.9–0.9)	< 0.001	1(0.997–1.003)	0.948
Age at onset of substance use	0.9 (0.9–0.9)	< 0.001	0.997(0.974–1.019)	0.768

In the multivariable logistic regression model adjusting for socio-demographic characteristics, substance-use–related variables, and duration of substance use, increasing age remained independently associated with lower odds of pregabalin use (adjusted OR = 0.90, 95% CI 0.90–0.90; p < 0.001). Religious practice of Sikhism continued to be associated with higher odds of pregabalin use compared with non-Sikhism (aOR = 1.5, 95% CI 1.1–2.1; p = 0.014), while rural residence remained protective (aOR = 0.7, 95% CI 0.5–0.9; p = 0.014). Employment status emerged as a significant protective factor after adjustment, with employed individuals having lower odds of pregabalin use compared with unemployed individuals (aOR = 0.5, 95% CI 0.3–0.7; p < 0.001).

With respect to substance-use characteristics, compared with alcohol use disorder (AUD), individuals with opioid use disorder (OUD) had substantially higher odds of pregabalin use (aOR = 5.3, 95% CI 3.5–7.9; p < 0.001). Those classified under other substance-use categories showed higher odds in unadjusted analysis; however, this association did not remain statistically significant after adjustment (aOR = 1.8, 95% CI 0.9–3.6; p = 0.081). Duration of substance use and age at onset of substance use were not independently associated with pregabalin use in the adjusted model.

Discussion

Gabapentinoids, developed originally as anticonvulsant medications, gained popularity for the management of peripheral neuropathy and other neuropathic pains as well as for anxiety [25]. Consequent to the reports of a substantial increase in the sales of gabapentinoids in the US and aggressive and improper marketing by manufacturers brought to the fore the non-medical use of this group of medications [25]. However, there is a scarcity of data from Southeast Asian countries including India. Thus, we conducted the present study, which is amongst the first few from India that evaluates the prevalence of pregabalin non-medical use and dependence in patients with substance use disorders seeking treatment at North Indian tertiary care hospitals located in different regions of Punjab and UT of Chandigarh. We report certain crucial findings. First, we observed a very high prevalence of non-medical use and dependence of pregabalin amongst individuals seeking treatment for substance use disorders. Second, pregabalin use was higher in those using opioids, with a young onset of substance use and with a shorter duration of substance use. Third, a high number of participants depicted a dependence pattern as observed in substance use disorders. Lastly, there were significant disparities in the socio-demographic and clinical characteristics of the participants.

The reported high prevalence of pregabalin non-medical use in our study concurs with the global estimates that that range from 1.6% to 6.6% in the general population and up to 68% in those with a substance use disorder [26–29]. In the present study, we found the prevalence of pregabalin non-medical use to be 44.7%% which is in the range of previous studies conducted among patients seeking treatment for substance use disorders [15, 16, 25, 28–31]. However, the rates of an ICD-10 dependence use disorder on pregabalin is very high in the index study (24.8%) as compared to a previous Indian study from same region [18]. An uprising trend of non-medical use of gabapentinoids has been reported in various European countries, Saudi Arab, and Australia [16, 29, 31, 32]. However, these estimates are much higher than those reported in some other studies [11, 18, 33–39].

We observed that pregabalin non-medical use and dependence was higher in those using opioids, with a young onset of substance use and with a shorter duration of substance use. In one of the earliest reports of non-medical use of pregabalin, the mean age of patients was reported to be 29 years (Range- 18–51 years) who consumed pregabalin in the range of 300-4200 mg/day (taken up to 6 times a day) [14]. Patients reported getting “high” akin to “amphetamine trip”, getting tolerance which led to need for an increase in dose as well as intoxication which required hospital admission for “detoxification”. A recent study conducted at a tertiary care hospital in Chandigarh reported mean age to be 28.45 years [18]. We also found similar age group for the patients who were using pregabalin and nearly two thirds of the study participants were consuming pregabalin in the dose range of 300 to 2400 mg per day (63.6%). Further, the daily consumption was even higher (> 1200 mg/day) for those who consumed pregabalin in a dependent fashion. These findings are also in keeping with the recently published study from India [18] except that patient consuming pregabalin in the present study hailed from rural background, were educated more than 10 years and earned more than 10,000 INR/month.

In a qualitative research conducted amongst non-medical users of pregabalin in Jordan, it was found that pregabalin use was common in poly-drug users (cannabis, benzodiazepines, opioids etc.), aged 21–30 years, who were introduced to pregabalin by a friend, sought it as an alternative to tramadol [16]. Some used it for treatment of addiction, as a legal substitute to another drug of use or to manage cannabis withdrawal. Poly-pharming was also common, and most of the participants were using it for less than a year. However, nearly half of them used it on a daily basis, knew about its negative consequence on health and social functioning, but did not know about its dependence producing effects. Self-detoxification led to withdrawal symptoms in form of exhaustion, headaches, anxiety, depression, joint and muscle pains, shivering, lethargy, and avoidance of social interaction. Pregabalin was being procured from the community pharmacies, without the need of a prescription and often patients were aware of the brand names only. In the index study too, most of the study participants consumed more than one substance along with pregabalin and majority consumed one or other forms of opioids with similar age range. The purpose of using pregabalin was to seek relaxation or relief from pain, euphoria/high, enhance the effect of other substance of use or a combination of these. Some sought pregabalin as an alternative to heroin or when they were unable to buy their primary substance of use. Nearly two third of patients in our study group were introduced to pregabalin by their friends and they bought it from community pharmacies without legible prescription.

Akin to developing dependence on a psychoactive substance, nearly one fourth (22.8%) of the index study participants met ICD-10 criteria for a dependence syndrome and reported an increase in dose of pregabalin over time, not getting the same effect with same doses of pregabalin, having withdrawal effects, and difficulty in cutting down the use of pregabalin and that the use of pregabalin affected their social functioning and health. A study from Germany which evaluated pregabalin use amongst the patient’s seeking treatment at a detoxification facility also reported similar rates of use of pregabalin (56%) and that 11% met DSM-IV criteria for dependency. Further, they reported the primary reason of pregabalin non-medical use to overcome the opioid withdrawal or augmenting the effect of another psychotropic substance [29]. Other researchers have also reported an increased use of pregabalin/gabapentin as a substitute to opioids, enhance the effect of other drugs or when the primary drug of choice was not accessible or manage the withdrawal symptoms of opioids [11, 18, 40, 41].

Critical policy implications and recommendations are emerging from our study. The evidence generated from the current representative survey raises concerns necessitating an urgent intervention to timely tackle this problem. It is even more crucial to target those who are already suffering from another substance use disorder, especially opioids. Our clinical experience suggests that the problem is not limited to Punjab, and is also affecting the vulnerable populations in the neighbouring states of North India. Recently, some restrictions on the over-the-counter sale of Pregabalin have been imposed in certain districts of Punjab; it is still to be universally enforced. From the clinical perspective, it is difficult to manage patients with concurrent intoxication of both opioids and pregabalin, which calls for robust screening methods that help elicit pregabalin non-medical use. Hence, it is imperative to develop strategies for timely identification of pregabalin non- medical use (such as quantitative drug screening of pregabalin in urine or blood) in addition to formulation of evidence-based treatment strategies. Health practitioners, apart from Psychiatrists, should be made aware of the non-medical use/dependence potential of pregabalin. The changes cannot be realised without a multi-disciplinary concerted effort that are not limited by geographical boundaries to further strengthen the control of the sale of pregabalin and prevent diversion or non-medical use/dependence of pregabalin.

Lastly, the present study has its strengths and limitations that should be acknowledged. The inclusion of a large representative sample from different regions of Punjab and Chandigarh, use of standardized tools to evaluate substance use disorders, and meticulous data collection are some of the major strengths of this study. However, the study is limited by its cross-sectional design, reliance on subjective report of various substances of use and lack of a method to confirm presence of pregabalin in the urine samples of the study participants. Lastly, despite the selection of a large representative sample from Punjab and Chandigarh, the findings of the study cannot be generalized for general population and specifically to other states of India.

Conclusion

Our findings project a grim situation of pregabalin non-medical use/dependence in patients with substance use disorders seeking treatment across different regions of Punjab and UT of Chandigarh. Nearly half of the patients seeking treatment for substance use disorders at major tertiary care hospitals located in different regions of Punjab and Chandigarh has non-medical use of pregabalin and nearly one fourth consumed it in a dependent manner. Further, young males, with younger onset of substance use disorder, especially an opioid use disorders, who were from rural background were more likely to use pregabalin. These findings seek attention of the healthcare providers and policy makers for need of more vigilance, screening for pregabalin non-medical use, formulate treatment strategies and devise policy changes to address diversion of pregabalin in view of its non-medical use potential. Future research from different regions of country shall be undertaken and valid measure of evaluation of pregabalin in blood or urine to be devised to assist in screening/diagnosis of pregabalin non-medical use.

Abbreviations

ASSIST

Alcohol, Smoking, and Substance Involvement Screening Test

AUD

Alcohol use disorder

CI

Confidence Interval

GABA

ɣ-aminobutyric acid

ICD-10

International Classification of Diseases, Tenth Revision

N

Number

OR

Odds ratio

OUD

Opioid use disorder

SD

Standard Deviation

SPSS

Statistical Package for Social Sciences

SUD

substance use disorder

US

United States

UT

Union Territory

VGCC

Voltage-gated calcium channels

WHO

World Health Organization

Author contributions

Category 1- a) Conception & Design: J.A., N.B., A.S., R.G., S.G., M.V. b) Acquisition of Data: J.A., N.B., A.S., R.G., S.G., S.K., L.G., I.D., R.B., B.U., J.S. c) Analysis and Interpretation of Data: J.A., M. V., S.K. Category 2a) Drafting the article: J.A., M.V. b) Revisions: J.A., M.V.,S.K., N.B., A.S., R.G., S.G. Category 3d) Final Approval: J.A., N.B., A.S., R.G., S.G., S.K., B.U., J.S., M.V., L.G., I.D., R.B.

Funding

Nil.

Data availability

The data may be obtained from the authors through electronic communications.

Declarations

Ethics approval and consent to participate

The research was approved by Institutional Ethics Committee vide IEC/AIIMS/BTI/396, dated 05-08-2023. A written signed informed consent was obtained as per the WHO Guidelines and the study followed Good Clinical Practice Guidelines.

Consent for publication

All the authors have consented.

Competing interests

The authors declare no competing interests.