Measuring pain in oral lichen planus: a comparative study of four assessment scales and their correlation

Abstract

Oral lichen planus is a chronic disease of the oral mucosa, with pain as one of its main symptoms. This study aimed to assess the correlation between the results of four pain intensity measures—including the Visual Analog Scale (VAS), Numeric Rating Scale (NRS), Short Form McGill Pain Questionnaire (SF-MPQ), and Verbal Rating Scale (VRS)— in a population of patients diagnosed with oral lichen planus. In this prospective observational study, 66 patients with oral lichen planus participated. Four pain assessment scales were used, including VAS, NRS, VRS, and SF-MPQ. Participants completed these assessments at baseline and again after two weeks of treatment. A paired t-test, Spearman correlation, linear regression analysis, and adjusted multiple regression analysis (regarding age and level of education) were used to analyze the data. All four scales were sensitive to changes in pain after treatment and a significant reduction in pain scores was observed (p < 0.001). There was a strong positive correlation between all scales (p < 0.001). Regression analysis showed that scores on each scale could significantly predict scores on the other scales (p < 0.001). Multiple regression analysis adjusted for age and level of education, showed the correlations between the pain scales remained strong and significant (p < 0.001). These commonly used pain assessment scales showed strong correlation with each other, and it seems that the results obtained from each might be comparable with the others. However, further researches in larger studies and different populations are needed.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-026-51605-9.

Introduction

Oral Lichen planus (OLP) is a chronic T-cell-mediated inflammatory disease¹. Its prevalence in the general adult population is approximately 5%, and women are affected twice as often as men^2,3. While the exact etiology of OLP remains unknown, it is believed to result from a multifactorial process⁴. The T-cell-mediated dysregulated immune response to specific antigens triggers an increase in the expression of cytokines, chemokines, and adhesion molecules, contributing to keratinocyte cell death, destruction of the mucosal basement membrane, and the disease’s chronic nature⁵.

OLP is mostly characterized by white reticulations (Wickham striae), erosion, and ulcerations⁶. Erosive and especially ulcerative forms of OLP are usually symptomatic, ranging from mild sensitivity to significant pain that impacts quality of life⁷. For many patients, OLP significantly limits essential daily activities, such as eating, drinking, speaking, and social interactions⁸. The World Health Organization has classified OLP as an oral potentially malignant disorder (OPMD)⁹. Currently, treatment of OLP focuses on reducing lesions and symptoms and increasing the duration of symptom-free periods^10–12. A meta-analysis that compared different interventions concluded that topical corticosteroids were the most effective treatment modality¹³.

Assessing the severity and extent of signs and symptoms associated with OLP is crucial for establishing baseline metrics and monitoring disease progression and treatment responses over time. Since different studies utilize various scales to assess pain following interventions for OLP, systematic reviews comparing these interventions need to aggregate the results effectively. There are several established scales for measuring pain, and in research studies, one or a combination of these scales is typically employed. A review study evaluating the effectiveness of three pain assessment scales, Visual Analog Scale (VAS), Numeric Rating Scale (NRS), and Verbal Rating Scale (VRS), across various diseases found that all three are both reliable and valid¹⁴. However, their specific relationship in patients with OLP remains insufficiently characterized, and if they are equally sensitive to changes over time following treatment. Furthermore, the potential interchangeability of these scales in clinical and research settings for OLP has not been established.

Therefore, this study aimed to assess the correlation between the results of pain intensity measures, including the VAS, NRS, VRS, and Short Form of the McGill Pain Questionnaire (SF-MPQ), to examine whether the outcomes of different treatment modalities for OLP suggested in clinical trials could be compared. Also, their sensitivity to changes in a population of patients with OLP was assessed.

Materials and methods

This prospective observational study follows the guidelines of the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement¹⁵.

The sample size was determined for Spearman’s rank correlation using the Fisher z-transformation method. Assuming a moderate correlation (ρ = 0.34), a two-sided significance level of 0.05, and 80% power, the calculation showed that a minimum of 64 participants were needed. To account for an anticipated 10% attrition or missing data, the target sample size was increased to 70 participants. Eighty-five consecutive patients referred to the Department of Oral and Maxillofacial Medicine of Tabriz Faculty of Dentistry diagnosed with OLP were examined for eligibility. Of these, 70 were confirmed eligible and included in the study, and 66 completed the follow-up, and were analyzed.

The inclusion criteria were age over 18 years and confirmation of the diagnosis of OLP both clinically and histopathologically based on the diagnostic criteria of the American Academy of Oral and Maxillofacial Pathology, 2016². Only newly diagnosed patients who had not received previous treatments were included. The main clinical diagnostic features used were the presence of painful, erythematous, erosive and ulcerative lesions, accompanied by Wickham’s striae and/or white papules on the mucosa². The histopathology confirmation was based on band-like or patchy, predominantly lymphocytic infiltrate in the lamina propria confined to the epithelium-lamina propria interface, basal cell hydropic degeneration, lymphocytic exocytosis, absence of epithelial dysplasia and absence of verrucous epithelial architectural change². Exclusion criteria included lesions exclusively adjacent to and in contact with dental restorations, lesion onset correlated with medication use², patients with asymptomatic OLP, patients with a history of opioid use and pregnant women.

Demographic information, including age, gender, educational level, underlying diseases, medications used, and disease manifestations, including ulcers and erythema, were obtained and recorded. Pain severity questionnaires were provided to the patients by a single researcher during both visits, and the results were recorded.

For NRS, patients were asked to indicate a numerical score indicating the severity of their symptoms on a scale of 0 to 10, with 0 being no symptoms and 10 being the worst imaginable symptoms¹⁶. For VAS, a 100 mm horizontal line was presented. The patient was informed that the left end of the scale indicated “no pain”, and the right end indicated “the most severe pain imaginable”. The patient was then asked to mark their pain on the line¹⁷.

For VRS, the participants were asked to mark the adjective that best matched the intensity of the pain. Between these two terms, different adjectives describing different levels of pain intensity are placed in order of pain intensity. To convert words into numbers for analysis, VRS was scored as follows: ‘no pain’ = 0, ‘mild pain’ = 1, ‘moderate pain’ = 2, and ‘severe pain’ = 3¹⁸.

SF-MPQ consists of a pain rating index (PRI), a present pain index (PPI), and a visual analog scale (VAS). For the PRI, the patient was asked to describe the sensory and emotional characteristics of his or their experience. The descriptors were rated on a pain intensity scale: 0-none, 1-mild, 2-moderate, or 3-severe². The PRI is the sum of the intensity values ​​of the descriptors that characterize pain. The PPI is a six-point scale (six options): from 0 (‘no pain’) to 5 (‘excruciating pain’)¹⁹.

Patients were prescribed a topical corticosteroid-containing mouthwash (a combination of 10 betamethasone ampoules with AL. Mg syrup and diphenhydramine syrup) every 8 h for 2 weeks. The patients were instructed to swish 15 ml of mouthwash for one minute and spit it out. They were instructed to return any remaining mouthwash at the follow-up session. The remaining volume of the mouthwash was measured to assess patient compliance.

The patients’ pain severity was again assessed during the next visit (after 2 weeks) using the aforementioned scales. The correlation between these changes was then examined on different scales.

Statistical analysis

The rate of change in pain intensity was calculated for each scale. Paired-samples T-test was used to compare the values ​ at two different time points. Also, to examine the agreement between pain scales, after converting the first- time scores of the instruments into standardized z-scores, the Bland-Altman method was used. The Spearman correlation statistical method was used to examine the correlation and agreement between the four pain assessment scales: NRS, VAS, VRS, and SF-MPQ. Linear regression analysis was used to assess the scales’ predictive ability and examine changes in pain scores. Adjusted multiple Linear regression analysis was used to adjust the effect of confounders like age and level of education. All statistical analyses were performed using SPSS version 18 and Medcalc software.

Results

A total of 66 patients were included. The mean age of patients was 51 ± 6.4. Thirty people were ≤ 50 years old and 36 were > 50 years old. Among these individuals, 60 were female (91%), and 6 were male (9%). In terms of education level, 20 were at the sub-diploma level (30.3%), 27 had a high school diploma (40.9%), and 19 had university degrees (28.8%). All patients had ulcerative and erosive form of OLP. Of the 66 patients included in the study, 5 had hypothyroidism and were on levothyroxine therapy. The remaining participants were generally healthy and used only supplements, such as calcium.

To clarify the relationships between these scales, the normal distribution function of each scale before and after the intervention is plotted in Fig. 1 (assuming that the data are normal).

Fig. 1.

The normal distribution function of the scales before and after the intervention (The first round is shown with a solid line, and the second round (after the intervention) is shown with a dotted line and a hatched surface).

The correlation coefficient between the first and second calculation times was acceptable in all of these scales, and all had a significance level of < 0.001. Next, a paired t-test analysis was performed between the first and second calculation of each scale, and it was found that all of these scales were significantly able to assess the differences found in the measurements and reached a significant level (P-value < 0.001) (Table 1).

Table 1.

Mean Pain scores differences (± SD) and correlation coefficient between baseline and post-treatment times across assessment scales.

Pain scale	Time 1	Time 2	Mean Differences ± SD	95% Confidence Interval	r	P-value5
VAS1	4.13 ± 1.56	1.19 ± 1.66	2.93 ± 1.46	2.57–3.29	0.59	< 0.001
NRS2	3.80 ± 1.40	1.03 ± 1.51	2.77 ± 1.41	2.42–3.11	0.53	< 0.001
VRS3	1.75 ± 0.63	0.57 ± 0.74	1.18 ± 0.72	1.00-1.35	0.46	< 0.001
SF-MPQ4	1.95 ± 0.84	0.56 ± 0.76	1.39 ± 0.80	1.19–1.59	0.51	< 0.001

¹Visual Analog Scale (VAS), ²Numeric Rating Scale (NRS), ³Verbal Rating Scale (VRS); ⁴Short Form McGill Pain Questionnaire (SF-MPQ);⁵Paired T-test.

The results of Spearman analysis showed a positive and significant correlation between the first-time scores of all scales (P-value < 0.001). Further, the results showed that there is a positive and significant correlation between the second-time scores (after the intervention) of all scales (P-value < 0.001). Subgroup analysis regarding the level of education in three groups (sub-diploma, diploma, university) and the age in two groups (> 50, ≤ 50) showed that correlation was more than 0.7 in all scores (p < 0.01), which means they strongly predict each other.

Linear regression analysis

The results of Linear regression analysis for the first session showed that the visual analog scale (VAS1) scores were highly correlated with the other pain scales (Table 2). Specifically, the NRS1 scores strongly predicted the VAS1 (R² = 0.65, B = 0.90, p < 0.001), indicating a strong relationship between the two scales. Also, the VRS1 and SF-MPQ1 scores were also significantly predictive of the VAS1 (R² = 0.62, B = 1.95, p < 0.001 and R² = 0.53, B = 1.35, p < 0.001).

Table 2.

Linear regression analysis predicting baseline pain scores across assessment scales.

Dependent variable	Predictor	R Square5	B6	SE7	p-value
VAS11	NRS1	0.65	0.90	0.082	< 0.001
	VRS1	0.62	1.95	0.189	< 0.001
	SF-MPQ1	0.53	1.35	0.157	< 0.001
NRS12	VAS1	0.65	0.72	0.066	< 0.001
	VRS1	0.52	1.60	0.192	< 0.001
	SF-MPQ1	0.49	1.16	0.148	< 0.001
VRS13	VAS1	0.62	0.32	0.031	< 0.001
	NRS1	0.52	0.32	0.039	< 0.001
	SF-MPQ1	0.44	0.49	0.070	< 0.001
SF-MPQ14	VAS1	0.53	0.39	0.046	< 0.001
	NRS1	0.49	0.42	0.054	< 0.001
	VRS1	0.44	0.89	0.12	< 0.001

¹Visual Analog Scale (VAS), ²Numeric Rating Scale (NRS), ³Verbal Rating Scale (VRS); ⁴Short Form McGill PainQuestionnaire (SF-MPQ); ⁵R Square values indicate the amount of variance explained in the dependent variable bythe predictor variable; ⁶Regression coeffi cient (B) indicates the strength of the relationship between the predictorand dependent variable; ⁷standard error.

The results of the second round of measurements showed a similar pattern (Table 3). The correlation between the variables was still high and significant. VAS2 was fully predicted by NRS2 with (R² = 0.67, B = 0.91, p < 0.001). Also, VRS2 and SF-MPQ2 were able to predict VAS2 changes well (R² = 0.63, B = 2.00, p < 0.001) and (R² = 0.54, B = 1.37, p < 0.001).

Table 3.

Linear regression analysis predicting post-treatment pain scores across assessment scales.

Dependent Variable	Predictor	R Square5	B6	SE7	p-value
VAS21	NRS2	0.67	0.91	0.07	< 0.001
	VRS2	0.63	2.00	0.19	< 0.001
	SF-MPQ2	0.54	1.37	0.16	< 0.001
NRS22	VAS2	0.67	0.73	0.06	< 0.001
	VRS2	0.53	1.62	0.19	< 0.001
	SF-MPQ2	0.50	1.18	0.15	< 0.001
VRS23	VAS2	0.63	0.33	0.03	< 0.001
	NRS2	0.53	0.33	0.03	< 0.001
	SF-MPQ2	0.44	0.51	0.07	< 0.001
SF-MPQ24	VAS2	0.54	0.40	0.04	< 0.001
	NRS2	0.49	0.43	0.05	< 0.001
	VRS2	0.44	0.90	0.17	< 0.001

¹Visual Analog Scale (VAS), ²Numeric Rating Scale (NRS), ³Verbal Rating Scale (VRS); ⁴Short Form McGill Pain Questionnaire (SF-MPQ); ⁵R Square values ​​indicate the amount of variance explained in the dependent variable by the predictor variable; ⁶Regression coefficient (B) indicates the strength of the relationship between the predictor and dependent variable; ⁷standard error.

Further examining the mean scores of the first and second-time points, the results of the linear regression analysis showed that the relationships between the pain scales remained strong and significant (Table 4). Specifically, the mean VAS scores were significantly predicted by the mean NRS (R² = 0.82, B = 1.02, p < 0.001), indicating a very strong association between the two scales. In addition, mean VRS and SF-MPQ scores were also able to predict mean VAS changes with coefficients (R² = 0.81, B = 2.20, p < 0.001) and (R² = 0.70, B = 1.72, p < 0.001), respectively.

Table 4.

Linear Regression Analysis Predicting Pain Scores Using the Mean of Baseline and Post-Treatment Measurements.

Dependent variable	Predictor	R square5	B6	95% CI	p- value
Mean VAS1	Mean NRS	0.82	1.02	0.90–1.14	< 0.001
	Mean VRS	0.81	2.20	1.93–2.46	< 0.001
	Mean SF.MPQ	0.70	1.72	1.44-2.0	< 0.001
Mean NRS2	Mean VAS	0.82	0.80	0.71–0.90	< 0.001
	Mean VRS	0.77	1.90	1.64–2.16	< 0.001
	Mean SF.MPQ	0.68	1.50	1.25–1.76	< 0.001
Mean VRS3	Mean VAS	0.81	0.36	0.32–0.41	< 0.001
	Mean NRS	0.77	0.40	0.34–0.45	< 0.001
	Mean SF.MPQ	0.73	0.72	0.61–0.82	< 0.001
Mean SF.MPQ4	Mean VAS	0.70	0.41	0.34–0.47	< 0.001
	Mean NRS	0.68	0.45	0.37–0.53	< 0.001
	Mean VRS	0.73	1.02	0.87–1.17	< 0.001

¹Visual Analog Scale (VAS), ²Numeric Rating Scale (NRS), ³Verbal Rating Scale (VRS); ⁴Short Form McGill Pain Questionnaire (SF-MPQ); ⁵R Square values ​​indicate the amount of variance explained in the dependent variable by the predictor variable; ⁶Regression coefficient (B) indicates the strength of the relationship between the predictor and dependent variable.

Adjusted multiple regression

In this model of regression, age and level of education were adjusted as confounding variables. The results showed that the relationships between the pain scales remained strong and significant (p < 0.001). The results of adjusted multiple regression for VAS (as a dependent variable) are reported in Table 5 as a sample, the other scales showed a similar pattern.

Table 5.

Multiple linear regression analysis adjusted for age and education level for predicting baseline, post treatment and mean score of vas pain score by other assessment scales.

Dependent variable	Predictor	B5	95% CI	SE6	P-value
VAS11	NRS12	0.91	0.74–1.08	0.06	< 0.001
	VRS13	1.99	1.60–2.38	0.19	< 0.001
	SF-MPQ14	1.35	1.03–1.68	0.16	< 0.001
VAS2	NRS2	1.02	0.91–1.13	0.06	< 0.001
	VRS2	2.06	1.84–2.29	0.11	< 0.001
	SF-MPQ2	1.95	1.70–2.20	0.12	< 0.001
Mean-VAS	Mean-NRS	1.03	0.91–1.15	0.06	< 0.001
	Mean-VRS	2.24	1.96–2.51	0.14	< 0.001
	Mean - SF.MPQ	1.72	1.43-2.00	0.14	< 0.001

¹Visual Analog Scale (VAS), ²Numeric Rating Scale (NRS), ³Verbal Rating Scale (VRS); ⁴Short Form McGill Pain Questionnaire (SF-MPQ); ⁵Regression coefficient (B) indicates the strength of the relationship between the predictor and dependent variable; ⁶Standard Error (SE).

Discussion

The present study assessed the correlation of the four pain assessment scales - VAS, NRS, VRS, and SF-MPQ - in patients with OLP. The mean difference between the first and second measurements showed a significant reduction in pain across all four scales (VAS, NRS, VRS, and SF-MPQ), indicating their usefulness in tracking the effectiveness of interventions. These findings are consistent with a review by Williamson et al. that confirmed the reliability and suitability of the VAS, NRS, and VRS for pain assessment¹⁴. However, the present study goes further by examining their use in OLP.

NRS and VAS are suitable for patients who can communicate verbally or in writing about their pain. In contrast, VRS is better suited for older people, children, or those with writing difficulties. NRS, and VRS are quick and easy to administer, imposing minimal burden on patients and clinicians, making them well-suited for routine clinical practice. However, VRS can lead to the misunderstanding that intervals between each descriptor are equal, which could be a source of error¹⁸. Although VAS is widely used it can be difficult for some patients such as elderly, and those with cognitive impairment²⁰. On the other hand, the SF.MPQ is particularly effective in assessing chronic pain but may take longer to complete¹⁷. The Likert scale relies on the patient’s choice of words and may be more challenging for some patients to comprehend. While providing richer qualitative information about pain characteristics, the SF-MPQ requires more time and patient engagement, which may limit its routine clinical use but make it valuable in research settings²¹.

OLP is a chronic disease with fluctuating symptoms, and reliable scales for assessing pain are crucial for monitoring disease progression and treatment effectiveness. A significant positive correlation was observed between the four pain scales at both baseline and post-treatment assessments. This suggests that despite their unique formats, these scales are generally convergent in assessing pain intensity in patients with OLP. These strong correlations are consistent with the findings of Chinani et al., who reported moderate to high correlations between VAS and NRS in patients with OLP²². However, the lack of a significant correlation between VAS and NRS reported by Rosas et al. in 2017¹⁶ suggests that the relationship between pain scales may vary depending on the specific population studied. This variability highlights the need to consider contextual factors and patient group characteristics when selecting a pain assessment scale. Otakhoigbogie et al. showed there was a significant strong, positive correlation between VAS and scales in dental patients. However, the correlation between SF-MPQ-2 and either VAS/NRS was weak but positive and statistically significant²³.

The results showed a high predictive power of each scale for the other scales. This means that scores on one scale can be used to estimate scores on another with reasonable accuracy, although not completely. For example, VAS scores can be predicted by NRS, VRS, and SF-MPQ scores and vice versa. Therefore, pain assessment scales have high predictive power relative to each other. Also, the mean scores of the scales showed a similar pattern of relationships. These results indicate that the scales overlap in assessing pain intensity and can be used as relative substitutes for each other in clinical research and interventions. However, each scale’s conceptual differences and unique characteristics should be considered when interpreting the findings. These results are consistent with the studies of Williamson¹⁴ and Hirmstad²⁰, who both showed that all three scales, VAS, NRS, and VRS, have high validity and reliability and in addition to high correlations between them, scores on one can predict scores on the other with acceptable accuracy. The predictive relationships discovered through regression analysis also suggest that it may be useful to use multiple scales simultaneously to gain a more comprehensive understanding of a patient’s pain experience. Each scale may address distinct aspects of the pain phenomenon, such as intensity, quality, or location, and combining these perspectives can increase the validity of the assessment.

Chinani et al. examined the competence of VAS and NRS scales in assessing OLP patients concerning the severity of disease symptoms. They observed a moderate to high correlation between these scales²². Also, a study by Lopez et al. examined the correlation of the VAS scale with patients’ clinical symptoms, and their results showed a significant correlation between this scale and the severity of clinical manifestations²⁴. In a study conducted by Park et al. in 2012, they examined the correlation between the NRS scale and the severity of clinical manifestations of reticulation, ulceration, and erythema in OLP patients. They concluded that the correlation between the severity of these clinical manifestations and the aforementioned scale was significant²⁵. On the other hand, Rosas et al. examined the correlation between VAS and NRS in patients who had felt any type of pain in the past thirty days. Contrary to previous studies, they did not observe a significant correlation between these two scales in pain perception¹⁶.

This study had some limitations. First, clinical sign data were not consistently available for all patients in this study, which limited our ability to perform a reliable correlation analysis. The data in this study were collected based on a specific sample, and the generalizability of the results to other population groups may be limited. Confounding factors such as psychological status, patient cooperation, and environmental conditions during assessment might influence the results. Although the same order of administration of pain measures was used for all patients, the pain measures were administered consecutively to the same patients in one session; therefore, the score obtained from the first scale may have affected the subsequent scores, resulting in a potential bias. Furthermore, the follow-up period in this study was short (two weeks), limiting its ability to evaluate the long-term reliability of these scales.

It is suggested that future studies examine the relationships between pain scales in different population groups. Also, using more objective methods such as biological biomarkers or brain imaging can help better understand the mechanisms of pain perception. Longer follow-up periods are also recommended. Finally, future studies can examine the influence of individual and environmental factors on selecting appropriate pain assessment scales to improve the accuracy of clinical assessments. Future studies should also focus on factors that can influence pain perception in patients with OLP, including psychological factors such as stress and anxiety that may modulate the experience of pain.

Conclusion

These commonly used pain assessment scales showed strong correlation with each other, and it seems that the results obtained from each might be comparable with the others. However, further researches in larger studies and different populations are needed.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contributions

KK contributed to the conceptualization of the study. PS performed the statistical analyses and interpreted data; MF and KK contributed to the data collection. NSh, KK, MF and PS contributed in writing and revising the manuscript. All authors read and approved the final version of the manuscript and agreed to be responsible for all aspects of the study including the accuracy of the work done.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Data availability

The datasets used and analyzed during the current study are available from the corresponding author upon reasonable request.

Declarations

Competing interests

The authors declare no competing interests.

Ethics approval and consent to participate

This study has been performed in accordance with the Declaration of Helsinki and has been approved by the Ethics Committee of Tabriz University of Medical Sciences (IR.TBZMED.DENTISTRY.REC.1403.026). We confirm that all methods were performed in accordance with the relevant guidelines and regulations. At the time of enrollment, written informed consent to participate in the study was obtained from participants (or their legal guardians in the case of illiterate participants). The steps of the study were explained to the participants, and people who filled out the informed consent were included. They were free to leave the study anytime and for any reason.