Analysis of Liver Injury Risk Factors in a Multiethnic Population Treated With Antituberculosis Drugs
Conditions: Tuberculosis Infection
Sponsor: Stefania Cheli

 
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CLINICAL STUDY PROTOCOL 
 
 
Project title: Analysis of liver injury risk factors in a multiethnic population 
treated with antituberculosis drugs 
 
Protocol code: TUBILI 
 
Study Drug: Isoniazid 
 
 
Version: 1.0 / 26.01.2024 
 
 
Principal Investigator: Dott. Alessandro Torre 
 
 
 
 
 
 
 
 
 
 
 
 
Statement Of Principal Investigator 
 
I have read this protocol and I agree to conduct this clinical study in accordance with all 
stipulations of the protocol and in accordance with the current regulations. 
 
 
 
Principal Investigator                                   Signature                                      Date 
 
Alessandro Torre                                                                                        19/02/2024  
                                                 
 
 
 

 
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Summary 
 
 
List of abbreviations ........................................................................................................................................ 3 
Abstract ............................................................................................................................................................ 5 
Risk factors associated with hepatotoxicity ............................................................................................ 6 
Factors Associated with Drug ............................................................................................................... 6 
Drug Biotransformation, Detoxification, and Elimination .................................................................. 6 
Factors Associated with Hosts ............................................................................................................ 10 
Rationale and Aims ...................................................................................................................................... 13 
Methods .......................................................................................................................................................... 14 
Study design .............................................................................................................................................. 14 
Study population ....................................................................................................................................... 14 
Data collection ........................................................................................................................................... 15 
Statistical analysis ........................................................................................................................................ 15 
Sample size calculation ........................................................................................................................... 15 
Data management ........................................................................................................................................ 17 
Potential Benefit of the Study ...................................................................................................................... 18 
Study Management & Coordination ........................................................................................................... 18 
Study Timeline ............................................................................................................................................... 19 
Ethical Considerations ................................................................................................................................. 19 
 
 
 
 
 
 

 
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List of abbreviations 
 
5-OH-PA 
5-Hydroxy Pyrazinoic Acid 
5-OH-PZA 
5-Hydroxy-Pyrazinamide 
ALT 
Alanine Transaminase 
AST 
Aspartate Transaminase 
ATDH 
Anti-Tuberculosis Drug-Induced Hepatotoxicity 
BIL 
Bilirubin 
BMI 
Body Mass Index 
COVID-19 
Corona Virus Disease 19 
CYP2E1 
Cytochrome P450 2E1 
CYP3A 
Cytochrome P450 3A 
CYP3A4 
Cytochrome P450 3A4 
CYP450 
Cytochrome P450 
DILI 
Drug-Induced Liver Injury 
DNA 
Deoxyribonucleic Acid  
eCFR 
electronic Case Report Form 
EMB 
Ethambutol  
FDA 
Food and Drug Administration 
GDPR 
General Data Protection Regulation 
GWAS 
Genome Wide Association Study 
HAART 
Highly Active Anti-Retroviral Therapy 
HAV 
Hepatitis A Virus 
HBV 
Hepatitis B Virus 
HCV 
Hepatitis C Virus 
HIV 
Human Immunodeficiency Virus 
INH 
Isoniazid  
NAD 
Nicotinammide adenina dinucleotide 
NAT2 
N-acetyltransferase 2 
OR 
Odds Ratio 
PA 
Pyrazinoic Acid 

 
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PI 
Principal investigator 
PK 
Pharmacokinetic 
PXR 
Pregnane X Receptor 
PZA 
Pyrazinamide  
RMP 
Rifampicin  
STR 
Streptomycin 
TB 
Tuberculosis 
TBI 
Tuberculosis Infection 
ULN 
Upper Limit of Normal range 
WHO 
World Health Organization 
XO 
Xanthine Oxidase 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
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Abstract 
 
Tuberculosis is the world’s second leading cause of death from a single infectious agent in 2022, 
after COVID-19 [1]. In 2022, TB disease was estimated to affect 10.6 million people, from which 1.3 
million dead because of it, despite the WHO adoption of the End TB Strategy [1] [2]. The 
standardised therapy involves a treatment regimen of INH, RMP, PZA, EMB, for 2 months, then INH 
and RMP for at least an additional 4-7 months [3]. Even though 85% of TB cases are successfully 
treated, significant morbidity from treatment-related adverse events, such as hepatotoxicity, skin 
reactions, gastrointestinal, and neurological disorders, reduces the efficacy of therapy [4] [5] [6]. In 
11% of patients receiving INH, RMP, and PZA in combination, hepatotoxicity is the most frequent 
adverse effect that results in drug discontinuation [5] [7] [8]. One of the most prevalent subtypes of 
idiosyncratic hepatotoxicity is caused by anti-TB drugs [4] [9] [10]. Numerous variables, including the 
features of the specific cohort, the drug regimens used, the employed threshold to define 
hepatotoxicity, and the monitoring and reporting procedures, influence the incidence of anti-TB drug-
induced hepatotoxicity. Overall, 5%–28% of patients receiving anti-TB drugs have experienced 
hepatotoxicity associated with the drug [4] [10]. It is difficult to determine how many of these fit the 
recent international consensus definition of DILI [9]. The majority of reports have defined 
hepatotoxicity as an elevated level of AST or ALT that is three times the ULN when symptoms (such 
as abdominal pain, nausea, vomiting, unexplained fatigue, or jaundice) are present, or five times the 
ULN when symptoms are absent [5]. Up to 20% of patients receiving INH as monotherapy or 
combination therapy for TB may experience a transient, asymptomatic elevation in liver enzymes; 
however, it usually resolves without drug discontinuation [11] [12] [13]. ATDH may manifest as 
asymptomatic elevations in liver enzymes or even as fulminant liver failure [5] [14]. In accordance to 
these results, the most commonly observed DILI pattern is the hepatocellular one [15]. Anti-TB drugs 
related hepatotoxicity is of great concern not only because of its frequency but also because of its 
severity and outcome. The median interval between starting a course of anti-TB treatment and the 
onset of clinical symptoms is 16 weeks (range 6 weeks-6 months) [16] [17] [18]. Despite decades of 
use and a large number of patients exposed to anti-TB drugs worldwide, the pathogenesis underlying 

 
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hepatotoxicity remains poorly understood. Further research investigating drug-related, host genetic, 
and environmental factors associated with susceptibility to hepatotoxicity, as well as additional 
studies searching for potential mechanisms leading to DILI, may be able to help clinicians develop 
strategies that reduce the incidence of hepatotoxicity and other adverse effects. 
 
Risk factors associated with hepatotoxicity 
 
Factors Associated with Drug 
 
Since most patients receive a combination of medications during their anti-TB therapy, it can be 
difficult to estimate the incidence of hepatotoxicity caused by individual agents. INH, RMP, and PZA 
are known to cause hepatotoxicity, whereas EMB is not thought to be hepatotoxic. Low risk of DILI 
has been shown by studies where RMP has been used alone in the treatment of TB infection [19] 
[20]. The most commonly reported drug associated with liver toxicity is INH [21]. According to four 
large population-based observational studies, the incidence of INH hepatotoxicity ranges from 0.1% 
to 0.56% when used as monotherapy to treat TB infections [16] [22]. A review based on FDA data 
estimated that 23.2 deaths per 100,000 patients receiving prophylactic therapy based on INH have 
occurred [23]. In a meta-analysis, INH was more likely to be associated with hepatotoxicity (odds 
ratio, OR 1.6), even in the absence of RMP [24]. However, when compared to each drug alone, the 
combination of these two was associated to a higher rate of hepatotoxicity (OR 2.6) [24]. The risk of 
hepatotoxicity has not been demonstrated to be higher for daily dosing regimens than for regimens 
that are administered three times a week [25]. 
 
Drug Biotransformation, Detoxification, and Elimination 
 
Reactive metabolites formation has been associated with several types of clinical toxicities, including 
some of those classified as idiosyncratic DILI [26]. In general, reactive metabolites are electrophiles, 
and, to escape detoxification, they interact with nucleophilic groups located on cellular proteins, 
especially at the level of lysine and cysteine [27]. Immune-mediated injury can also result from the 
production of reactive metabolites following covalent protein binding [28]. Cellular proteins with 

 
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covalent modifications should be degraded or repaired: failure of these processes results in the 
manifestation of target organ injury due to drug-metabolite adduct formation that compromises 
important cellular functions. An elevated concentration or an enhanced activity of the enzymes 
catalysing the biotransformation of a drug into a reactive metabolite may increase the level of 
reactive metabolites formation in an individual. Generally, these are phase I CYP450 enzymes 
involved in oxidation, reduction, or hydrolysis. Another reason of drug toxicity may be ascribed to 
low concentrations or reduced activity of those enzymes required to detoxify reactive metabolites. 
Generally, detoxification occurs through the processes of acetylation, sulfation, glucuronidation, or 
glutathione conjugation, which are mediated by phase II enzymes. Water soluble metabolites are 
excreted into bile or in the systemic circulation with the contribution of transporter molecules or 
proteins, which mediate phase III of drug disposition. Since the majority of first-line anti-TB drugs are 
lipophilic, they need to be biotransformed into water soluble compounds before being eliminated. 
Rather than being the direct result of the parent drug's action, hepatotoxicity seems to be related to 
the production and accumulation of reactive metabolites [29] [30]. 
 
Isoniazid 
 
INH is primarily metabolised in the liver. NAT2 and the microsomal enzyme CYP2E1 are the principal 
enzymes involved in INH metabolic pathway and therefore they are crucial in determining the 
greatest risk of hepatotoxicity. NAT2 converts INH to acetyl isoniazid, followed by hydrolysis to acetyl 
hydrazine. This latter could be oxidised by CYP2E1 to produce N-hydroxy acetyl hydrazine, which 
then undergoes additional dehydration to produce acetyl diazine. Acetyl diazine can be a toxic 
metabolite in and of itself, or it may breakdown into reactive acetyl radicals, acetyl onium ions, and 
ketene, which, in turn, can covalently bind to hepatic macromolecules and cause injury to the liver. 
Additionally, acetyl hydrazine is further acetylated by NAT2 to produce nontoxic diacetyl hydrazine 
[31] [32]. Thus, mono acetyl hydrazine and the parent compound accumulate as a consequence of 
slow acetylation [33]. INH itself further inhibits the acetylation of acetyl hydrazine. Furthermore, the 
production of hydrazine through direct hydrolysis of INH without acetylation increases the risk of liver 
injury [34], as observed in slow acetylators which show ten-fold increased INH metabolism through 

 
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this pathway, especially when combined with rifampicin [35]. The human hepatic NAT2 enzyme 
exhibits a highly polymorphic nature. One or more wild-type, referred to as NAT2*4, alleles are 
associated with rapid acetylator status, whereas slow acetylators are characterised by the presence 
of any two of several variant alleles [36]. By in vitro experiments, it has been observed that 
acetylation activity gradually decreases according to the presence of a specific allelic variant, in the 
following order: NAT2*4 > NAT2*7 > NAT2*6 > NAT2*5 [37]. Genetic polymorphisms in metabolism 
account for 88% of the drug's PK variability, with a linear relationship between isoniazid clearance 
and number of high-activity NAT2 alleles [38] [39]. Due to the reduced metabolism, slow acetylators 
show higher plasma levels and lower drug clearance than rapid acetylators [40] [41] [42]. In several 
studies [43] [44] [45] [46] [47], NAT2 slow acetylator profiles (or two slow NAT2 alleles) have been 
associated with an increased risk of hepatotoxicity/liver injury/hepatitis caused by anti-TB drug 
treatment when compared to rapid acetylators. Due to the existence of common loss of function 
polymorphisms in NAT2 and the important contribution of acetylation to INH metabolism, there have 
been a large number of studies examining these variants as INH-induced hepatotoxicity risk factors 
in tuberculosis patients [48] [49] [50]. With an overall OR ranging from 1.59 to 6.42 and, although 
the risk varied depending on the specific genotypic definition of slow acetylation and the population 
under study, at least four meta-analyses, including a significant number of cases, have concluded 
that slow acetylators have an increased risk of DILI [46] [49] [51] [52] [53] [54]. Furthermore, slow 
acetylators were more likely to experience severe hepatotoxicity, with respect to rapid acetylators. 
In particular, compared to other genotypes, NAT2*6/6 and NAT2*6/7 variants are associated to 
reduced enzymatic activity and significantly higher risk of liver injury. In accordance with many 
candidate gene studies in several ethnic groups, a recent GWAS identified NAT2 as the most 
important risk factor for ATDH in the Thai population [55]. Based on available data, it appears that 
reactive metabolites are the cause of INH hepatotoxicity. Several studies on the mechanism of INH 
hepatotoxicity have highlighted the role of immune-mediated idiosyncrasy, described as the 
mechanism of the liver's adaptive responses to INH, and the heterogeneity of the clinical picture of 
INH hepatotoxicity [56] [57].  

 
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Rifampicin 
 
After oral administration on an empty stomach, RMP is rapidly and completely absorbed. In the liver, 
RMP is metabolised into desacetyl rifampicin by desacetylation [58] [59], and a separate pathway of 
hydrolysis produces 3-formyl rifampicin [59] [60]. The metabolic derivative, desacetylrifampicin, is 
more polar than the parent compound, and microbiologically active. This metabolite is indeed 
responsible for the majority of the antibacterial activity in the bile. RMP is almost equally excreted in 
bile and urine, with recovery rates on the same order of magnitude. All RMP metabolites are non-
toxic, however, RMP is considered able to induce hepatocellular patterns of DILI and to increase 
toxicity of other anti-TB drugs, like INH [58] [59] [61]. RMP is known as the activator of PXR, a ligand-
activated transcription factor that plays a crucial role in the metabolism of xenobiotics and 
endobiotics in mammals [58] [62]. Indeed, PXR regulates the expression of drug-metabolising 
enzymes and transporters, as well as genes involved in endobiotic metabolism, by binding to its DNA 
response elements. In particular, PXR positively influences the expression of the major Phase I 
enzymes, CYP450s. Via PXR, RMP induces several metabolic enzyme pathways, particularly the 
CYP3A4 system [63] [64]. CYP3A4 activation produces, indeed, an increased metabolism of INH, 
resulting in toxic metabolites, therefore explaining the anti-TB drug induced hepatotoxicity of RMP. 
When used in combination with INH, RMP also induces INH hydrolysis, leading to increased 
hydrazine production, and increasing its toxicity, especially for slow acetylators [35]. 
Pyrazinamide 
 
PZA is an analogue of nicotinamide, which is a vitamin B3 (nicotinic acid, also called niacin) 
precursor. PZA is mainly metabolised in the liver by amidase, which converts PZA to PA [65]. XO 
further oxidises PA to 5-OH-PA [66] [67]. Alternatively, PZA can be hydrolysed by amidase to form 
5-OH-PA, after first being oxidised by XO to 5-OH-PZA. Moreover, trace amounts of pyrazinuric acid 
can be produced when PA and glycine conjugate. Kidney excretion is the primary route of elimination 
for PZA and its metabolites [68] [69]. PZA has a longer half-life than both INH and RMP; moreover, 
it has been observed that PZA half-life increases, when taken with other drugs that inhibit XO, such 
as allopurinol, and in presence of an underlying liver disease [68] [69]. The extent of PZA 

 
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hepatotoxicity is associated with its hepatic metabolism, suggesting a direct toxic effect rather than 
an immunological or hypersensitive response [5] [69] [70]. PZA hepatotoxicity is also dose-
dependent, particularly at daily doses exceeding 40 mg/kg. In murine models, PZA inhibited CYP450 
activity [71] and changed NAD levels [72], leading to free radical species-mediated hepatotoxicity.  
Fluoroquinolones 
 
According to current WHO guidelines, fluoroquinolones are the most valuable second line anti-TB 
agents in case of multi-drug resistant TB and hepatotoxicity from first line agents [73]. Quinolones 
are either excreted unaltered by the kidneys (for example, levofloxacin) or metabolised in the liver 
(such as ciprofloxacin). Except for trovafloxacin, which is currently withdrawn, fluoroquinolone-
induced hepatotoxicity is extremely rare and can only be identified by extensive research or 
international pharmacovigilance reporting [74]. There have been isolated reports of ciprofloxacin, 
levofloxacin, and gatifloxacin-related severe hepatotoxicity [75]  [76], and hypersensitivity reactions, 
which are frequently associated to peripheral eosinophilia and fever, are assumed to be the cause 
of hepatotoxicity [77]. When fluoroquinolones were administered to patients with underlying chronic 
liver disease whose hepatitis was brought on by first-line anti-TB drugs, there was no further 
hepatotoxicity [78]. It has been also observed that ofloxacin is safe and effective when used in 
patients who already have liver diseases [79]. 
Factors Associated with Hosts 
 
Several risk factors for the development of hepatotoxicity have been suggested from a multitude of 
studies, but robust conclusion cannot be drawn due to significant variations in study design, cohort 
size and case definition. 
Age 
 
A correlation between age and a higher risk of DILI has been traced. Age over 60 has been 
associated to a 3.5-fold increased risk of DILI in a study involving 519 patients receiving standard 
anti-TB drugs [80]. In another study with 430 patients, the incidence of pyrazinamide-related adverse 
events, such as DILI, was 2.6 times greater in over 60 individuals [78]. Furthermore, among a cohort 

 
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of more than 3000 patients receiving INH monotherapy, those with 50 years of age or older showed 
a higher frequency of DILI [16]. There have also been reports of increased mortality rates associated 
with INH hepatotoxicity beyond the age of 50 [23] [29] [81]. Patients who experienced DILI with anti-
TB drugs were found to be older (39 years) in a case-control study than those who did not (32 years) 
[82]. A multivariate analysis revealed that the only independent variable that could predict anti-TB 
DILI in over 35 patients was their age, with a rate of 17% respecting a rate of 33% in patients over 
35 [83]. Moreover, advancing age is characterised by pharmacokinetic changes, including a 
reduction in renal and hepatic clearance and an increase in volume of distribution of lipid soluble 
drugs [84]. All these changes lead to a prolongation of plasma elimination half-life. In contrast, an 
older meta-analysis [24] found that children receiving INH and rifampicin had a higher incidence of 
clinical hepatitis (6.9%) than adults (2.7%). The inclusion of three small studies, each with 22–60 
patients, however, significantly contributed to the high frequency of DILI in children by reporting a 
high frequency of "clinical hepatitis" in 25–52% of all patients.  
Gender 
 
Anti-TB therapy has been shown to increase the risk of DILI in women [78] [85] [86], with a reported 
4-fold increase [87]. Females are indeed more susceptible to hepatotoxicity due to higher CYP3A 
activity [88]. Moreover, it has been observed that in the third trimester of pregnancy and in the first 
three months after giving birth, there is a trend towards an increased risk of INH hepatotoxicity [89]. 
Status of Nutrition 
 
Malnutrition is common in TB patients and has been related to an increased risk of anti-TB drugs 
hepatotoxicity [90]. According to a recent retrospective observational study [91], a highly significant 
independent risk factor for DILI is a weight loss of 2 kg or more occurring during the first 4 weeks of 
TB treatment. Given that fasting and malnutrition have an impact on cytochrome P450 enzyme 
system, TB drug detoxification is ensured by receiving adequate amounts of nutrients, therefore 
preserving liver metabolism integrity [92]. 
 

 
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Alcohol Intake 
 
Liver injury may be caused by both the direct toxicity of alcohol metabolic by-products and the 
inflammation induced by the by-products themselves. Numerous studies showed that alcohol 
extended the hepatotoxicity caused by anti-TB drugs [93] [94] [95]. Even patients receiving rifampicin 
as a preventative treatment have been shown to be at risk [96] [97].  
Concomitant Infection 
 
It has been suggested that mild inflammatory reactions caused by co-existing viral infections can 
frequently function as a "danger signal", allowing the development of early events in the 
pathophysiological process into a full-blown hepatotoxic reaction; this can be explained by the 
increased level of drug hypersensitivity in these patients [98]. Several cohorts have been examined 
to determine whether chronic infections other than tuberculosis raise DILI risk during anti-TB therapy. 
The risks of drug- and virus-induced hepatitis were significantly higher in patients with high initial 
viral load than those with low initial viral load and those without viral hepatitis (39% vs 10.5% of HBV 
patients and 33% vs 16.7% of HCV patients, p<0.001) [99]. This study has also demonstrated a 
direct correlation between the viral load at the onset of anti-TB therapy and the severity of 
hepatotoxicity [99]. Comparable to HBV infection, 30% of all HCV-infected patients receiving anti-
TB medication developed hepatotoxicity, whereas 11% of controls had a 5-fold relative risk of 
hepatotoxicity development and severity directly related to the viral load [100]. Additionally, there is 
a significant increased risk of hepatotoxicity from anti-TB drugs when HIV infection coexists. This 
has been observed both prior to and during the highly active HAART era. Hepatotoxicity ranged from 
4 to 15% in the pre-HAART period and from 4 to 27% in the HAART era [101]. Nevertheless, a 
number of confounding factors have been identified, including the use of intravenous drugs, 
alcoholism, viral hepatitis, hepatotoxicity due to HAART therapy, drug–drug interactions, and liver 
damage caused by immune reconstitution [101]. 
 

 
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Rationale and Aims 
 
Patient's susceptibility to DILI during treatment with anti-TB drugs is influenced by several drug- and 
host-related factors [102]. The most extensively studied potential causes of INH-induced DILI are 
related to those mechanisms. As to drug-related factors, acetylhydrazine, which is generated by 
NAT2, is widely considered as a crucial INH metabolite that contributes to INH-induced DILI. Given 
the importance of acetylation in INH metabolism, several studies have investigated into NAT2 loss 
of function polymorphisms as possible risk factors for DILI. In addition, advanced age [94], female 
gender [86], poor nutritional status [103], HBV or HCV infection [100] [104], HIV infection [78] [105], 
chronic liver disease, and alcoholism are environmental, physiological, and pathological factors 
contributing to DILI incidence. Moreover, the influencing variables differ according to racial and 
geographic characteristics. 
Studies conducted in China demonstrated that approximately one-third of DILI patients had no 
symptoms, including some cases with severe liver injury [106] [107]. It has been demonstrated that 
screening patients for risk factors is useful in preventing disease progression, improving the outcome 
of therapy, and reducing mortality. However, rapid acetylators are very common in the Chinese 
population, so they are characterised by a lower susceptibility to develop DILI. Our patient cohort is 
multi-ethnic, with a prevalence of Caucasians and so a higher frequency of slow acetylator status. 
For this reason, our objective is to corroborate the conclusions drawn by the previous studies through 
the examination of our complementary data. 
 
Outcome measures and assessments  
 
The primary outcome is to determine the association between risk factors (drug- and host-related 
factors) and the incidence of DILI.  
The primary outcome measures are the occurrence of anti-TB DILI (number of participants with DILI), 
which was defined by: 1) AST or ALT level > 5 times the ULN in patients with absence of symptoms 
or with total BIL level > 2 times the ULN, or 2) AST or ALT level > 3 time the ULN and total BIL level 
> 3 times the ULN in patients who show symptoms compatible with hepatitis. 

 
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The secondary outcome is to evaluate the characteristics of patients who first experienced anti-TB 
DILI. The secondary outcome measures are the prevalence of early hepatotoxicity experience. 
Methods 
 
Study design 
 
This is a retrospective observational study, no profit, to determine environmental, physiological, and 
pathological factors associated with the incidence of DILI during anti-TB treatment. Data collected 
from patients with confirmed tuberculosis, enrolled at the Department of Infectious Diseases of Luigi 
Sacco Hospital in Milan, Italy, between July 2020 and September 2023, will be analysed. Subjects 
were all followed up as outpatients at Tuberculosis Clinic at Luigi Sacco Hospital, some of them with 
previous inward stays at various hospitals in the Lombardy Region. 
Study population 
 
The following are the inclusion criteria: 1) adult patients (>18 years), 2) patient who received standard 
initial therapy including INH (5mg/kg), RMP (10mg/kg), and PZA (25mg/kg) for patients with active 
TB disease, 3) treatment with first line anti-TB drugs, including rifampicin and isoniazid for patients 
with latent TBI, 4) normal serum ALT and bilirubin levels, no symptoms related to abnormal liver 
function prior to anti-TB drug treatment and 5) informed consent. Patients with any of the following 
conditions are excluded from the study: 1) liver dysfunction, including biliary origin, before anti-TB 
therapy, 2) patients receiving non-standard treatment regimen initially (e.g., patients with severe 
pulmonary or extrapulmonary TB receiving large doses or more than four anti-TB drugs), 3) modified 
treatment regimen due to drug resistance or intolerance excluding first line anti-TB drugs, 4) lactation 
or pregnancy, 5) concomitant use of hepatotoxic drugs, 6) abnormal hepatic function on laboratory 
testing before anti-TB, 7) disease that was resistant to INH at the start of treatment or 8) patients 
refusing to sign informed consent. 
The participants were given standard anti-TB treatment in line with international guidelines (RMP 10 
mg/kg, INH 5 mg/kg), primarily administered orally, although intravenous administration was 

 
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employed for inpatients as needed, and modified to oral administration as soon as possible. The 
other drugs of the standard regimen included standard daily doses of PZA (15-30 mg/kg) and EMB 
(15-20 mg/kg). 
Data collection 
 
Data that will be collected include clinical, biochemical, and genotyping findings that are typically 
used in clinical practice to manage and monitor tuberculotic patients at Luigi Sacco Hospital. The 
complete list of parameters (host- and drug-related factors) is provided below:  
• 
Clinical data: age, weight, height, gender, ethnicity, hepatotoxicity or alcoholism, duration of anti-
TB treatment, tuberculosis site (pulmonary or extra), adverse event, concomitant infection (HIV, 
HAV, HCV, HBV), past medical history, concomitant drugs. Patient`s nutritional status was 
reported as BMI, which was calculated based on height and body weight; 
• 
Biochemical data: ALT, AST, GGT and BIL; 
• 
Laboratory data: NAT2 acetylator status. The acetylation status of patients will be assigned like 
as suggested by earlier research: 
− 
rapid acetylator: NAT2*4 is a wild-type allele (defined by absence of slow alleles); 
− 
intermediate acetylator status: carry one copy of NAT2*4 and one defective variant allele 
(NAT2*5, *6, *7, and *14); 
− 
slow acetylator: two copies of slow variant allele (NAT2*5, *6, *7, and *14). 
Statistical analysis 
 
Sample size calculation 
 
We are planning a study of matched sets of cases and controls with 2 matched controls per case. 
Prior data indicate that the probability of exposure among controls is 50%, and the correlation 
coefficient for exposure between matched cases and controls is -0.2 [10] [108] [109] [110] [111]. If 
the true odds ratio for disease in exposed subjects relative to unexposed subjects is 3, we will need 
to study 40 case patients with 80 matched controls to be able to reject the null hypothesis that this 

 
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odds ratio equals 1 with a power of 80%, assuming that the Type I error probability associated with 
the test of this null hypothesis is 5%.  
 
Parameters: Exposure in cases = 75%; Exposure in controls = 50% 
Absolute difference = 25%; Relative difference = 50%; Odds ratio = 3 
Sample sizes across range of OR and control exposure, with inputted values: 
 
Number of cases required varying ratio of controls per case, other inputs constant: 
We will use a nested case-control study design that takes into account time of events occurrence in 
sampling of controls. For each case, one or more controls are selected from the risk set at the time 
in which the event of interest occurred in the case. The risk set means the set of all individuals that 
are still “events-free” and not censored. Therefore, they are still included in the study at that time, 
thus, eligible to experience the event now observed in the case. As a consequence, individuals can 

 
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be sampled as controls for more than one case and, in turn, individuals sampled as controls may 
subsequently become cases. Cases and controls will be matched according to baseline variables, 
including age, sex, and BMI, and then conditional regression analysis (a type of matched statistical 
analysis) will be performed to draw associations. 
Data management 
 
All data are retrieved from the patient's medical record. Variables will be entered into the eCRF by 
site staff, who will be trained on how to use the eCRFs and capture the data required by the protocol. 
The eCRF is an electronic data entry media and should not constitute the original (or source) medical 
record. Data derived from source documents and reported in the eCRFs should be consistent with 
the source documents, or the discrepancies should be explained in these source documents. The 
investigator must complete the eCRF for each participant. The investigator’s signature on the eCRF 
will attest to their accuracy and completeness. 
Data collected from each participant will be anonymized: each subject will be assigned a unique 
code so that only the investigator will be able to identify the subject. The file associating the 
participant’s code with their identifying data will be stored separately on a password protected 
computer. The study database will be password protected and uploaded to a computer that is also 
password protected and accessible only to study personnel designated by PI. Identification of the 
data will be done in such a way that individuals accessing the database will not be able to trace the 
identity of the subjects in any way. 
The study will involve statistical calculations on collected data using literature standard methods to 
identify and correlate variables (Chi-square, Fisher's exact, Mann-Whitney U-test, conditional 
regression). The results will be published in medical journals and presented at conferences. Study 
data will be retained for 7 years starting from the study's conclusion. Data processing will be done in 
strict compliance with GDPR and any applicable national legislation.  
 

 
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Potential Benefit of the Study 
 
The data collected will provide important new perspectives on the management and prevention of 
DILI. Preventing serious hepatic failure requires early detection and prompt drug withdrawal, which 
is also a crucial step in managing adverse reactions. The diagnosis of DILI is based on the index of 
suspicion, the careful assessment of the temporal correlation between the exposure to a specific 
drug and the particular clinical event, and the exclusion of other possible diagnoses.  
For patients undergoing anti-TB treatment, hepatotoxic side effects represent significant obstacles. 
Indeed, DILI development can compromise treatment compliance, or lead to treatment interruption, 
or, again, result in disease relapse, or induce drug resistance; all these conditions will finally lead to 
treatment failure. Screening patients for risk factors is of great importance in preventing disease 
progression, improving therapeutic outcomes, and reducing mortality.  
Furthermore, patient’s re-exposure to the same drug regimen leads to DILI recurrence in 11%–30% 
of cases [112]. Compared with the initial event, DILI after rechallenge occurs more rapidly (generally 
after days or weeks) than after initial exposure [113]. DILI on rechallenge leads to jaundice in 64%, 
hospitalisation in 52%, and mortality in 13% of cases [114]. 
Combining host- and drug-related risk factors associated with the development of DILI might 
generate better tools to pre-empt or diagnose DILI, leading to better regimen tolerability and 
ultimately to a better treatment outcome. 
Study Management & Coordination 
 
PI with support from the working group's different specialists, is responsible for coordinating and 
accurately executing the study in compliance with the procedures outlined in this protocol. All study-
related documentation (including protocol, amendments, eCRF, database, partial and final reports) 
must be archived by PI. Each component of documentation will be preserved electronically. 
 

 
Version: 1.0 / 16 November 2023 
 
Study Timeline  
 
The study will start after obtaining approval from the Ethical Committee. Consequently, the duration 
will be computed for a total of three months, starting from the approval of this study protocol. 
Ethical Considerations 
 
The responsible investigator will ensure that this study will be conducted in accordance with the 
protocol, following the instructions and procedures described, adhering to the principles of Good 
Clinical Practice E6 (R2) and in compliance with principles established by the 18th World Medical 
Assembly (Helsinki, 1964 and further amendments) and with the laws and regulations of the country 
in which the research will be carried out, whichever offers the greatest protection to the individual. 
The observational study and related documentation will be submitted to the relevant Ethics 
Committee. 
The study will begin only after obtaining the required authorisations, in accordance with the internal 
procedures of the institution. 
 
 
 
 
 
 
 
 
 

 
Version: 1.0 / 16 November 2023 
 
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