Effects of orlistat on APRI and FIB-4 scores in patients with obesity: a retrospective observational study

Abstract

Objective

Metabolic dysfunction–associated steatotic liver disease (MASLD) is closely associated with obesity and diabetes mellitus (DM). Early identification of patients at risk of liver fibrosis is important for clinical management; however, liver biopsy is not routinely feasible, and fibrosis is therefore assessed using non-invasive surrogate indices. Orlistat is a widely used therapy for obesity, but its effects on non-invasive liver fibrosis scores remain unclear. This study aimed to evaluate changes in calculated fibrosis scores after orlistat treatment in patients with obesity.

Methods

Data were retrospectively collected from 335 patients diagnosed with obesity who initiated orlistat treatment. Laboratory parameters and body weight measurements were obtained at the baseline, and at the 3rd, 6th, and 12th months following orlistat treatment. Weight changes were also recorded. MASLD not confirmed by biopsy was evaluated using calculated fibrosis scores. The Fibrosis-4 (FIB-4) index and Aspartate Transaminase-Platelet Ratio Index (APRI) are used to assess fibrosis, and the data were also obtained at the same endpoints.

Results

Of the 335 patients at baseline, data were available for 310, 134, and 39 patients at 3, 6, and 12 months, respectively. A significant reduction in weight and body mass index (BMI) was observed following orlistat treatment (p < 0.01). Repeated-measures analysis showed no significant change in FIB-4 scores (p = 0.46), whereas APRI scores decreased significantly (p < 0.01). When patients were stratified by a 5% weight-loss threshold, no differential effect on changes in FIB-4 or APRI scores was observed. In multiple linear regression analysis, changes in fibrosis scores were independent of sex, baseline weight, weight change during follow-up, presence of diabetes mellitus, and use of metformin or sodium–glucose cotransporter-2 inhibitors.

Conclusion

Orlistat treatment resulted in significant weight loss and reductions in ALT and AST levels. While the APRI score decreased significantly with treatment, the FIB-4 score did not change significantly. The change in APRI score was independent of weight loss.

Introduction

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common cause of chronic liver disease and a leading contributor to morbidity and mortality. It is estimated to have a prevalence of 30% in the adult population and represents a significant global health concern [1]. The risk factors for MASLD, which has gained increased awareness following its recent reclassification, include obesity, insulin resistance, diabetes mellitus (DM), and hypertriglyceridemia. Its prevalence parallels the rising incidence of obesity. A meta-analysis has shown that the prevalence of MASLD in the obese population is 75% [2].

The clinical course of MASLD ranges from simple steatosis to steatohepatitis and progressive fibrosis, which ultimately determines long-term prognosis. Early identification of fibrosis is therefore a key component of patient management. Although liver biopsy remains the reference method for fibrosis assessment, its invasive nature, cost, and limited feasibility preclude widespread use in routine practice. As a result, non-invasive fibrosis scores such as the Fibrosis-4 (FIB-4) index and the Aspartate Aminotransferase/Platelet Ratio Index (APRI) are increasingly used, as they are inexpensive, readily available, and have demonstrated acceptable diagnostic performance in MASLD populations [3–5].

Weight reduction is the mainstay of MASLD treatment and has been consistently associated with improvements in hepatic steatosis and inflammation, while more substantial weight loss may also lead to fibrosis regression [5]. Pharmacological weight-loss therapies are therefore of interest in patients who fail to achieve adequate results with lifestyle interventions alone. Pioglitazone and glucagon-like peptide-1 receptor agonists (GLP-1 RAs) may reduce liver fat, serum aminotransferase levels, and fibrosis [6]. Orlistat, a gastrointestinal lipase inhibitor approved for obesity treatment, induces moderate weight loss and improves several metabolic parameters, including glycemic control and lipid profiles [7, 8]. However, its effects on liver fibrosis remain unclear, and data regarding changes in non-invasive fibrosis scores—particularly APRI—are scarce. In this study, we evaluated longitudinal changes in FIB-4 and APRI scores after initiation of orlistat therapy, with a specific focus on whether these changes occur independently of the degree of weight loss.

Materials and methods

Study design and patient selection

In this retrospective analysis, we reviewed the records of patients who began treatment with orlistat (120 mg three times daily) for obesity at our clinic between November 2022 and June 2024 and remained compliant with the prescribed therapy. Exclusion criteria included chronic liver disease, renal insufficiency, alcoholism, exogenous steroid use, the development of hepatobiliary diseases that could affect liver function during follow-up, and the use of pioglitazone and/or GLP-1 receptor agonists for the treatment of diabetes mellitus or obesity. A total of 335 patients who continued orlistat treatment for at least 3 months after initiation were included in the study. The flow chart of patient inclusion is illustrated in Fig. 1. The Ankara Etlik City Hospital Ethics Committee approved this study (Number: AEŞH-BADEK-2025-0101). Clinical trial number: not applicable.

Fig. 1.

Flow chart of patient inclusion

Clinical and laboratory measurement

Demographic data, medications, clinical characteristics, and duration of orlistat treatment for all patients were recorded. Initial plasma glucose, plasma insulin, creatinine, glycated hemoglobin (HbA1c), total cholesterol, LDL cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides, alanine aminotransferase (ALT), aspartate aminotransferase (AST), and platelet values were recorded where available. Pairwise deletion was applied, and analyses were conducted using all available data for each variable. During orlistat treatment, body weight, weight changes, and laboratory values, including ALT, AST, platelet count, total cholesterol, LDL cholesterol, HDL cholesterol, and triglyceride levels, were recorded at the 3rd, 6th, and 12th months. Of the 335 patients at baseline, follow-up data were available for 310, 134, and 39 patients at 3, 6, and 12 months, respectively. Analyses at each time point were conducted using only available data, without imputation. Patients were classified as having MASLD according to obesity and accompanying metabolic risk factors. At baseline, 40 of the 330 patients had elevated ALT and AST levels. Mathematically, FIB-4 and APRI scores were calculated. FIB-4 was calculated using the following formula: (Age [years] × AST [U/L]) / (Platelet count [10⁹/L] × √ALT [U/L]). APRI was calculated using the following formula: [(AST / upper limit of normal AST range) × 100] / Platelet count [10⁹/L]. Serum ALT and AST levels were measured using standard automated enzymatic assays in the same hospital laboratory.

Statistical analysis

The normality of the data was assessed using the Kolmogorov-Smirnov and Shapiro-Wilk tests, skewness and kurtosis, and graphical methods (histogram, Q-Q plot, stem-and-leaf plot, boxplot). For data with normal distribution, mean ± standard deviation was used, while median [interquartile range] was used for non-normally distributed data. Categorical variables were presented as count and percentage n (%). For continuous variables, Student’s t-test was used for normally distributed data, and Mann-Whitney U test was used for non-normally distributed data. The relationship between numerical variables was analyzed using Spearman’s correlation. For evaluating repeated measurements, a repeated-measures ANOVA was used for normally distributed variables, and the Friedman test was used for non-normally distributed variables. Mauchly’s test was applied to check the sphericity assumption for repeated measures ANOVA, and Greenhouse-Geisser corrections were applied when sphericity was violated. Post hoc pairwise comparisons were conducted with the Bonferroni adjustment when significant overall effects were observed. Multivariable linear regression analyses were performed to assess factors associated with changes in continuous fibrosis scores (FIB-4 and APRI). Results are reported as β coefficients with 95% confidence intervals, and statistical significance was defined as a p-value < 0.05. Given the exploratory nature of the analyses, no formal adjustment for multiple comparisons was applied.

Results

The median [interquartile range (IQR)] follow-up duration was 6.0 [3.0–8.0] months, with data available for 310 patients at the 3rd month, 134 patients at the 6th month, and 39 patients at the 12th month. Adverse effects of the medication, its cost, perceived insufficient efficacy, and insurance-related issues leading to treatment discontinuation, as well as loss to follow-up among patients who continued the medication, were the main reasons for the reduction in patient numbers. Among the patients included in the study, 296 (88.4%) were female, with an average age of 46.0 ± 12.1 years. The most common comorbidities were hypertension (24.8%) and diabetes mellitus (20.3%). The patients’ baseline demographic and laboratory data are presented in Table 1.

Table 1.

Baseline demographic, clinical, and laboratory characteristics of the study population

Sex, Female, n (%)	296 (88,4) / 39 (11,6)
Age, years	46,0 ± 12,1
Follow-up Duration, months	6,0 [3,0–8,0]
Comorbidities, n (%)	170 (50,7)
Hypertension, n (%)	83 (24,8)
Diabetes Mellitus, n (%)	68 (20,3)
Hyperlipidemia, n (%)	61 (18,2)
Atherosclerotic cardiovascular disease, n (%)	11 (3,3)
Medications, n (%)
Metformin (for DM or non DM), n (%)	199 (59,4)
Metformin Dose, miligram	2000 [1000–2000]
Does Not Use SGLT-2 Inhibitor, n (%)	301 (89,9)
Uses Empagliflozin, n (%)	19 (5,7)
Uses Dapagliflozin, n (%)	15 (4,5)
Obesity, n (%)
Class 1 Obesity, n (%)  Class 2 Obesity, n (%)  Class 3 Obesity, n (%)	3 (0,9) 13 (3,9) 319 (95,2)
Laboratory Values
Glucose, mg/dL	97,0 [87,0-108,0]
Insulin, mU/L	21,9 ± 13,5
HOMA-IR, index	4,5 [3,1–6,4]
Hemoglobin A1c, %	5,6 [5,2–6,4]
Total Cholesterol, mg/dL	190,9 ± 37,4
LDL Cholesterol, mg/dL	121,6 ± 31,9
HDL Cholesterol, mg/dL	48,0 ± 11,4
Triglycerides, mg/dL	151,2 ± 66,4
ALT, U/L	19,0 [14,0–27,0]
AST, U/L	18,0 [15,0–23,0]
Platelets, 106/µL	311,3 ± 76,8

Categorical variables are presented as n (%), normally distributed variables as mean ± standard deviation, and non-normally distributed variables as median [interquartile range]. Metformin was prescribed for diabetes mellitus or insulin resistance

DM: Diabetes mellitus, SGLT-2: Sodium–Glucose Cotransporter 2, HOMA-IR: Homeostasis Model Assessment of Insulin Resistance, LDL: Low-Density Lipoprotein, HDL: High-Density Lipoprotein, ALT: Alanine Aminotransferase, AST: aspartate aminotransferase

Body weight and BMI significantly decreased at the 3rd, 6th, and 12th months during orlistat treatment. Patients who lost more than 10% of their weight were 18.4%, 53.7%, and 74.4% at the 3rd, 6th, and 12th months, respectively. These patients experienced an average weight loss of 15.9 ± 9.6% over the 12 months of treatment. Although fasting LDL cholesterol and triglyceride levels decreased during follow-up, this change was not significant (Table 2).

Table 2.

Changes in anthropometric, metabolic, and fibrosis parameters during follow-up

Parameter	Baseline (n = 335)	3 Months (n = 310)	6 Months (n = 134)	12 Months (n = 39)	p-value
BMI, kg/ m2	43,7 [40,8–47,0]	40,9 [38,4–45,0]	38,9 [36,0–43,2]	38,9 [33,3–42,3]	< 0,01
Weight, kg	112,0 [104,0-124,0]	105,0 [96,0-118,3]	101,0 [89,8-112,3]	92,0 [85,0-112,0]	< 0,01
Weight change from baseline, kg		-7,4 ± -5,2	-13,0 ± -7,4	-18,4 ± -11,5	< 0,01
Weight change from baseline, %		-6,4 ± -4,3	-11,3 ± -6,2	-15,9 ± -9,6	< 0,01
Percentage of Weight Loss
<%5, n (%)		123 (39,7)	11 (8,2)	3 (7,7)
%5–10, n (%)		130 (41,9)	51 (38,1)	7 (17,9)
>%10, n (%)		57 (18,4)	72 (53,7)	29 (74,4)
LDL Cholesterol, mg/dL	121,6 ± 31,9	114,5 ± 30,5	113,0 ± 30,7	110,6 ± 19,3	0,54
Triglycerides, mg/dL	151,2 ± 66,4	157,0 ± 79,4	140,7 ± 58,8	126,4 ± 64,5	0,24
FIB-4, score	0,600 [0,434-0,863]	0,623 [0,453-0,833]	0,640 [0,455-0,854]	0,570 [0,395-0,720]	0,46
FIB-4 change from baseline, score		-0,007 [-0,114–0,081]	-0,036 [-0,121–0,101]	-0,038 [-0,168–0,085]
APRI, score	0,189 [0,141-0,254]	0,184 [0,142-0,235]	0,175 [0,143-0,213]	0,145 [0,120-0,174]	< 0,01
APRI change from baseline, score		-0,012 [-0,047–0,026]	-0,027 [-0,073–0,015]	-0,033 [-0,085–0,085]

Categorical variables are presented as n (%), normally distributed variables as mean ± standard deviation, and non-normally distributed variables as median [interquartile range]

BMI: body mass index, kg: kilogram, m²: square meter, LDL: Low-Density Lipoprotein, FIB-4: The Fibrosis-4 index, APRI: Aspartate Transaminase-Platelet Ratio Index

The baseline values of the non-invasive fibrosis models used for evaluation, FIB-4 and APRI scores, were 0.60 [0.43–0.86] and 0.18 [0.14–0.25], respectively. Baseline FIB-4 distribution showed that 93.1% of patients had scores < 1.3, 6.0% had scores between 1.3 and 2.67, and 0.9% had scores > 2.67. During follow-up, no significant change was observed in FIB-4 scores, while a significant decrease was observed in APRI scores (p = 0.46 and p < 0.01, respectively) (Table 2; Fig. 2). When comparing to baseline, reductions in APRI scores at the 3rd, 6th, and 12th months were statistically significant (p < 0.01, p < 0.01, and p < 0.01, respectively). The observed decrease in APRI scores is consistent with an improvement in fibrosis-related risk estimates over time. In multivariate regression analysis, changes in FIB-4 and APRI scores at the 3rd and 6th months were independent of gender, initial body weight, diabetes mellitus status, sodium-glucose cotransporter-2 inhibitor use, metformin use, and body weight change.

Fig. 2.

Time Course of APRI and FIB-4 Scores

Discussion

In this single-center study, a reduction in aminotransferase levels and non-invasive fibrosis scores was observed in patients receiving orlistat. These changes appeared to be independent of weight loss and suggest a potential benefit of orlistat in obese patients with MASLD. To our knowledge, this retrospective study of 335 patients is among the first to examine changes in APRI scores in this population.

Non-invasive liver fibrosis scores are increasingly used in clinical practice. In our study, FIB-4 scores did not change significantly, whereas APRI scores decreased significantly. The FIB-4 index has shown utility in screening for advanced fibrosis and cirrhosis, and may also serve as a prognostic marker for liver-related outcomes [9, 10]. Its performance, along with NFS, has been examined across different BMI categories; both scores are reliable for excluding advanced fibrosis in overweight, obese, and severely obese individuals, but their utility is limited in underweight and morbidly obese patients [11]. The lack of a significant change in FIB-4 in our study group may be attributed to the fact that 95.2% of our patients were classified as morbidly obese. In addition, FIB-4 includes age, which does not change during follow-up, along with AST, ALT, and platelet count, making it less sensitive to short-term changes. In contrast, APRI primarily reflects AST and platelet ratio, which may respond more quickly to improvements in metabolism and inflammation.

The observed APRI reduction was independent of weight loss, suggesting that orlistat may exert effects on hepatic inflammation or AST levels beyond its weight-reducing effects. However, it is important to note that patients with baseline APRI values below 0.5—indicating low fibrosis risk—may show only minimal improvement. Even modest reductions in APRI may still reflect favorable trends in hepatic inflammation or metabolic status. Supporting this concept, previous evidence suggests that hepatic steatosis is associated with increased pro-inflammatory cytokine activity, which may contribute to carotid intima–media thickening and early vascular remodeling [12]. The APRI score has been found to be significantly associated with metabolic-related cardiovascular risk, and it has been shown that an increase in APRI, especially in women, indicates an increase in cardiovascular risk [13, 14]. Given that 88.4% of our patients are women, the importance of the APRI score is even greater. The regression of this score, which is important not only for MASLD but also for cardiovascular outcomes, with treatment may suggest a potential benefit of orlistat in patients with obesity. However, potential confounders, including dietary changes, regression to the mean, and natural variability of AST, should be considered when interpreting these results.

Prospective studies have shown that a weight gain of more than 5 kg is associated with the progression of hepatic steatosis and fibrosis [15]. Current guidelines strongly recommend diet and exercise interventions to improve histologically or non-invasively assessed liver damage in overweight adults with MASLD.

Orlistat has been a long-established treatment for many years. In a study conducted by the European Multicenter Orlistat Study Group, the group receiving orlistat lost a significantly higher amount of weight, 10.2%, compared to the placebo group, which lost 6.1%, after one year [7]. A meta-analysis of 12 studies with a 12-month follow-up showed that orlistat resulted in approximately 8% weight loss [16]. In our cohort, weight loss was greater than reported in the literature, likely because patients who maintained weight reduction could continue orlistat through social insurance, promoting adherence.

Orlistat has been shown to reduce weight, ALT, AST, triglycerides, glucose, and HOMA-IR [17]. While some studies report non-significant changes in fasting lipids and glucose [18], a recent meta-analysis showed that orlistat significantly reduces liver fat, liver enzymes, BMI, total cholesterol, and LDL, though it may increase triglycerides [19]. Our findings similarly demonstrated improvements in lipid profile, suggesting that orlistat provides both weight loss and metabolic benefits in MASLD patients.

Results regarding orlistat’s effect on liver fat are mixed. MRI-based studies show greater reductions in liver fat with orlistat than with diet alone [20]. Biopsy studies in smaller cohorts, however, report limited histological improvement [21]. In our study, non-invasive liver fibrosis scores decreased during orlistat therapy, independent of weight loss. This suggests that mechanisms beyond weight loss might contribute to this benefit. Orlistat may also affect the incorporation of n-3 long-chain polyunsaturated fatty acids, which could influence liver inflammation [22]. In obese MASLD patients, a positive correlation was observed between reductions in liver fat infiltration and changes in serum periostin and adiponectin levels [23]. In addition, the spleen-liver axis and immune mechanisms may play a role in MASLD-related inflammation, suggesting other ways in which orlistat could benefit the liver [24]. For all these reasons, we believe that studies evaluating the relationship between orlistat treatment and inflammation would be beneficial.

A major limitation of this study is the substantial attrition over time, with the number of patients decreasing markedly by the 12-month follow-up. This loss may introduce attrition bias and limit the generalizability of long-term findings. However, this reflects real-world treatment discontinuation in obesity pharmacotherapy. The lack of liver ultrasound results and waist circumference follow-ups in the study are other limitation. The generalizability of our findings may be limited due to the high proportion of morbidly obese patients, the predominance of female participants, and potential selection bias, as patients who continued therapy may have been more adherent or responsive.

Despite these limitations, this study has several strengths. It was conducted in a large patient cohort, enhancing the robustness of the findings. Importantly, this study contributes novel data to the literature by examining changes in the APRI score in obese patients undergoing orlistat treatment. These results may serve as a foundation for future randomized controlled trials to further explore the effects of orlistat on liver health and metabolic outcomes.

Conclusions

These results led us to believe that orlistat treatment may provide metabolic benefits in addition to weight loss. A significant reduction in the APRI score was observed with treatment, independent of weight loss. The effects of orlistat on MASLD should be assessed through long-term follow-up studies that include histopathological parameters.

Author contributions

All the authors contributed to the study conception and design. HD, OB, CKU, and NKF collected the data. HD, SH, and BC performed data analysis and interpretation. HD wrote the main manuscript. BC, SH, and EC conducted the critical review. All the authors read and approved the final manuscript.

Funding

No funding was received for the conduct of this study.

Data availability

The data that support the findings of this study are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

The Ankara Etlik City Hospital Ethics Committee approved this study (Number: AEŞH-BADEK-2025-0101). The study was conducted in accordance with the principles of the Declaration of Helsinki. Due to the retrospective nature of our study, the Ethics Committee did not require informed consent for participation. Clinical trial number: not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.