INTRODUCTION

Actinic keratoses (AK) are premalignant epidermal lesions caused by chronic ultraviolet radiation (UV) on sun-exposed skin. Risk factors include older age, male sex, Fitzpatrick I–II phototypes, immunosuppression, and photosensitizing drugs such as hydrochlorothiazide. Epidemiological studies also implicate prolonged outdoor activity, light hair/eye color, and facial solar lentigines, while sunscreen use and higher BMI (≥25) offer partial protection [1,2].

A systematic review estimated a global prevalence of ~14%, with regional variation driven by UV exposure, skin type, and healthcare access [3]. Despite this burden, AK is frequently underdiagnosed and inconsistently managed. Lesion-targeted therapies dominate, field-directed approaches remain underused, and referral pathways are often inefficient [4].

Although clinically similar, AKs differ biologically. Confluent, hyperkeratotic “AK patches” carry higher malignant risk, whereas most lesions remain stable or regress. This variability underscores the need for individualized risk stratification [5,6].

The broad morphological spectrum—including flat, pigmented, and atypical forms—complicates diagnosis. Routine biopsies are impractical in patients with extensive damage [7]. Dermoscopy identifies characteristic features such as red pseudonetworks, perifollicular scaling, and the “strawberry pattern,” but limited depth restricts invasion assessment. Advanced non-invasive imaging (RCM, OCT, LC-OCT) provides near-histological resolution, aiding early detection of atypia [8,9].

Field cancerization, described by Slaughter et al. in 1953, denotes perilesional tissue with subclinical genetic change [10]. In AK, chronically sun-exposed skin shows UV-induced atypia and mutations, justifying field-based therapy [11]. Photodamage refers to benign visible changes (solar lentigo, seborrheic keratosis, telangiectasia) [12,13], while actinic field damage encompasses visible and subclinical alterations with malignant potential [14,15]. Photodamage is limited to clinically benign signs [16,17]; actinic field damage represents a continuum including histological or molecular dysplasia, invisible clinically but detectable by dermoscopy, histopathology, or biomarkers [18–20].

Commonly used clinical metrics, such as total lesion count (TLC), Physician Global Assessment (PGA), or composite AK burden scores, fail to reflect the underlying histological severity or subclinical field involvement [21]. Clinical grading systems, including the Olsen scale, correlate poorly with histopathological classification [22]. The Actinic Keratosis Area and Severity Index (AKASI) integrates both lesion burden and field involvement, and higher scores have been associated with an increased risk of progression to cSCC [23,24].

Genomic data show a multistep progression from AK to carcinoma, beginning with TP53 and NOTCH1 mutations, followed by CDKN2A, PIK3CA, FBXW7 alterations and MAPK, NF-κB, PI3K/AKT/mTOR dysregulation [25–27]. Figure 1 summarizes these histological, molecular, and immunologic changes.

Despite multiple therapies, lesion-directed approaches prevail. Cryotherapy, the most common, fails to address subclinical field cancerization and recurs frequently. Field-directed treatments such as PDT, imiquimod, and 5-FU provide broader control; among these, 5-FU shows superior clearance and long-term cSCC risk reduction [28–30].

The combined use of the Total Actinic Keratosis Burden Score (TABS) and the Field Index (FI) provides a quantitative, dermoscopy-based system that captures both lesion and field dimensions, thereby enabling more precise risk stratification and personalized therapeutic planning.

MATERIALS AND METHODS

RESULTS

A total of 200 participants were included (100 AK, 100 controls). AK patients were significantly older than controls (70.0 ± 11.1 vs. 64.6 ± 12.7 years; p = 0.0015). Sex distribution did not differ (p = 0.197), while Fitzpatrick phototypes showed significant differences (p < 0.001). Occupational UV exposure categories were comparable (p = 0.758). Dermoscopic field scores were significantly higher in the AK group (5.91 ± 1.71 vs. 4.70 ± 1.44; p < 0.001; Hedges’ g = 0.76). Detailed demographic and clinical data are summarized in Table 3.

Figure 5 illustrates sex-based differences in the anatomical distribution of AK lesions. Males most frequently exhibited lesions on the vertex, ears, and frontotemporal region, while females showed higher involvement of the cheeks, infraorbital, and nasal areas.

Among AK patients, the mean Lesion Score was 10.3 ± 2.0 and the mean Field Score was 5.9 ± 1.7, yielding a mean TABS of 16.2 ± 2.9 and an average FI of 36.2% ± 8.0. Based on predefined thresholds, most patients were classified as moderate burden (69%) with moderate field involvement (48%), while 15% showed severe field-dominant phenotypes. Detailed stratification is presented in Table 4.

Regression analyses showed that higher TABS values were significantly associated with older age (p = 0.011), while sex, Fitzpatrick type, and occupational UV exposure showed no consistent effects. Importantly, FI was not correlated with lesion number or region count, underscoring its independence from visible distribution. Patients with TABS ≥18 were significantly older and had higher field scores than those with lower TABS. Subgroup results are detailed in Table 5.

Combined analyses confirmed that age, occupational UV exposure, and region count were not significant predictors of severe field involvement (FI >45%). Region count showed poor discriminatory performance (AUC = 0.46). Correlation analysis revealed that lesion count correlated moderately with TABS (ρ = +0.34, p < 0.001) but not with FI, while age showed only a weak association with TABS (ρ = +0.25, p = 0.011). Full results are presented in Table 6.

DISCUSSION

This study assessed AK burden using the dermoscopy-based TABS and FI. These complementary tools capture both visible lesion severity and subclinical field damage, offering a more comprehensive assessment than traditional lesion counts. By integrating clinical, dermoscopic, and demographic data, the TABS–FI framework stratified AK patients into phenotypes reflecting the balance between focal lesions and background photodamage. The study included 200 chronically sun-exposed individuals (100 AK patients, 100 age- and sex-matched controls), allowing evaluation of demographic and clinical predictors of disease severity.

In our cohort, patients with AK had a mean age of 70.0 years, significantly higher than that of controls (64.6 years, p = 0.0015), confirming age as a key determinant of actinic damage. This observation aligns with epidemiological studies demonstrating a marked rise in AK prevalence with advancing age [35,36]. Although sex distribution did not differ significantly between groups (male/female: 63/37 vs. 53/47, p = 0.197), prior research has consistently shown a male predominance, commonly attributed to androgenic alopecia, greater occupational sun exposure, and less frequent photoprotection [37]. Fitzpatrick phototypes differed significantly (p < 0.001), with AK patients more often displaying lighter skin types, supporting meta-analyses that highlight elevated risk in phototypes I–II [38]. In contrast, occupational UV exposure categories showed no significant differences between groups (p = 0.758), diverging from multicenter reports linking high occupational sun exposure with increased AK burden. This discrepancy may reflect limitations of occupational classification or, more importantly, the predominant role of cumulative lifetime UV exposure and inherent skin type in shaping disease risk.

Analysis of lesion distribution showed clear sex-related patterns. In males, AKs were most common on the nose (44.4%), cheeks (38.1%), and ears (31.8%). In females, facial involvement predominated, particularly the cheeks (67.6%) and nose (54.1%). The high prevalence of auricular lesions in men agrees with prior studies, whereas the pronounced female facial predominance—possibly influenced by hair coverage, headwear, or cosmetic photoprotection—contrasts with reports of higher chest and leg involvement in other populations. These population-specific patterns underscore the need for preventive counseling tailored to anatomical sites most affected in each sex [39].

Occupational UV exposure categories did not differ significantly between AK patients and controls (p = 0.758). This diverges from multicenter European studies reporting increased AK risk with high occupational sun exposure. As Fartasch et al. highlight, both occupational and non-occupational (e.g., recreational) UV exposure must be considered, with cumulative lifetime dose likely more relevant than job categorization [40]. In our region, indoor workers often engage in secondary agricultural activities, and high ambient sunlight may blur categorical distinctions, explaining the absence of a clear occupational signal. These findings suggest that lifetime cumulative exposure and skin type exert stronger effects than current occupation.

Our findings highlight the clinical utility of the TABS–FI system in quantifying subclinical burden. In our cohort, the FI was diagnostically independent of visible lesion counts (ρ = −0.028, p = 0.780), confirming that lesion number alone fails to capture background photodamage. This is consistent with clinical trial evidence showing that visible lesion counts underestimate field cancerization, as topical 5-FU unmasks numerous subclinical lesions beyond baseline [41]. Imaging and histopathology likewise demonstrate photodamage extending beyond clinical borders, reinforcing AK as a continuum of visible and subclinical disease [42]. Notably, 15% of our patients exhibited severe field involvement despite few visible lesions, illustrating the ‘hidden burden’ emphasized in current S3 guidelines [43]. TABS also correlated positively with age (ρ = +0.254, p = 0.011), validating it as a pragmatic marker of cumulative UV exposure [44].

To enhance specificity, the TABS–FI model excludes benign UV-induced changes such as solar lentigines and seborrheic keratoses and instead focuses on dermoscopic features with premalignant potential. This is particularly relevant in pigmented variants, which may mimic melanoma or lentigo maligna and often require histopathology for confirmation [45,46]. By incorporating multiple lesion- and field-specific dermoscopic parameters, TABS–FI reduces diagnostic ambiguity and provides a standardized measure of premalignant burden.

Phenotypic stratification showed that the moderate FI phenotype was predominant (48%), indicating that intermediate subclinical field involvement represents the typical presentation. Although often underappreciated, this subgroup may still carry a measurable risk of progression to cSCC. Severe field-dominant disease was present in 15% of patients, supporting a proactive, field-directed approach. Notably, conventional variables—age, occupational UV exposure, and region count—failed to predict severe FI (AUC = 0.46), underscoring the limits of traditional risk tools. In contrast, the TABS tracked lesion number while remaining independent of FI, capturing both visible burden and cumulative photodamage. These observations are concordant with evidence that field therapies such as 5-FU and daylight PDT improve outcomes irrespective of baseline lesion counts [47,48]. Noninvasive imaging, particularly LC-OCT, further demonstrates that actinic damage extends beyond clinical margins [49,50], reinforcing the utility of FI-based stratification (Figure 6).

In our cohort, the TABS–FI system showed a mean FI of 36.2%, with 15% of patients exhibiting severe field-dominant phenotypes, indicating a substantial subclinical burden. These findings are consistent with molecular evidence of Notch pathway dysregulation and elevated NOTCH1 expression in AK, mechanisms that promote a pro-carcinogenic field [51,52]. Complementary imaging studies using ultraviolet-induced fluorescence dermoscopy also demonstrate that subclinical photodamage extends beyond visible margins, reinforcing the clinical value of FI-based stratification for detecting hidden actinic burden [53]. Together, histopathologic, molecular, and imaging data illustrate the continuum from benign photodamage to invasive squamous cell carcinoma, a progression exemplified in Figure 7.

Several indices have been developed to assess AK burden, including AKASI [54,55], AK-FAS [56], total lesion count [44], PAASI [57], MASCK [58], and more recently a composite clinical–dermoscopic–confocal scoring approach [59]. While each tool provides partial insight, they remain limited by reliance on clinical or photographic features, restricted anatomical scope, and lack of dermoscopic integration for quantifying subclinical field damage. In contrast, the TABS–FI model introduced here integrates lesion- and field-based dermoscopic criteria, enabling stratification into phenotypes such as moderate burden (69%) and severe field-dominant (15%), categories not captured by conventional tools. As summarized in Table 7, TABS–FI combines lesion–field balance, dermoscopic precision, and phenotype-based risk stratification, positioning it as a practical tool for personalized AK management.

Recent literature emphasizes that visible AK lesions represent only the ‘tip of the iceberg’ of UV-induced dysplasia. In our cohort, mixed-pattern phenotypes were common (41%), and 14% of patients demonstrated severe field-dominant involvement (FI >45%), confirming that substantial subclinical burden may exist even when visible lesion counts are low. This phenotype-based approach underscores the clinical value of TABS–FI and provides a basis for individualized management, consistent with guideline recommendations [60] and recent evidence linking high-risk AK phenotypes with increased cSCC potential [61]. Field-directed therapies such as daylight PDT, 5-FU, and tirbanibulin not only improve clearance but also reduce cSCC risk, as highlighted in updated reviews [62,63]. For patients with severe field damage, adjunctive tools such as RCM may be warranted, supported by systematic evidence for its role in treatment monitoring [64). Collectively, our findings reinforce the need to move from lesion-centric treatment to dermoscopy-guided, field-integrated strategies [65]. Figure 8 outlines the mechanistic basis of available therapeutic modalities, while Table 8 provides a phenotype-based framework for translating TABS–FI scores into individualized treatment planning.

CONCLUSION

This study introduces the dermoscopy-guided TABS–FI framework to comprehensively quantify both clinical and subclinical actinic keratosis burden. By moving beyond simple lesion counts and incorporating field assessment, the model provides more precise stratification of actinic damage. Our findings demonstrate that substantial subclinical involvement can be present even in patients with few visible lesions. TABS–FI offers a numeric, anatomically adaptable, and reproducible tool that may facilitate personalized management and enhance clinical risk stratification in AK.

ABBREVIATIONS

5-FU: 5-Fluorouracil

AK: Actinic Keratosis

AKASI: Actinic Keratosis Area and Severity Index

AK-FAS: Actinic Keratosis Field Assessment Scale

AUC: Area Under the ROC Curve

BMI: Body Mass Index

CI: Confidence Interval

cSCC: Cutaneous Squamous Cell Carcinoma

COX-2: Cyclooxygenase-2

DAMPs: Damage-Associated Molecular Patterns

DNA: Deoxyribonucleic Acid

dPDT: Daylight Photodynamic Therapy

FI: Field Index

GCP: Good Clinical Practice

IQR: Interquartile Range

IL-10: Interleukin-10

Ki-67: Marker of Cellular Proliferation

LC-OCT: Line-Field Confocal Optical Coherence Tomography

MAPK: Mitogen-Activated Protein Kinase

MASCK: Method for Assessing Skin Cancerization and Keratoses

MMPs: Matrix Metalloproteinases

NF-κB: Nuclear Factor Kappa B

OCT: Optical Coherence Tomography

OR: Odds Ratio

PAASI: Photoaging Area and Severity Index

PDT: Photodynamic Therapy

PGA: Physician Global Assessment

PI3K/AKT/mTOR: Phosphoinositide-3-Kinase/Protein Kinase B/Mammalian Target of Rapamycin pathway

RCM: Reflectance Confocal Microscopy

ROC: Receiver Operating Characteristic

ROS: Reactive Oxygen Species

SD: Standard Deviation

SOD: Superoxide Dismutase

SPC: Superficial Perivascular Capillary

TABS: Total Actinic Keratosis Burden Score

TGF-β: Transforming Growth Factor Beta

TLC: Total Lesion Count

TLR-7: Toll-Like Receptor 7

TP53: Tumor Protein p53

UV: Ultraviolet

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