Objective To explore the latent classes of pre⁃treatment disease uncertainty in patients with nasopharyngeal carcinoma (NPC) and their influencing factors. Methods A convenience sampling method was adopted to select 260 NPC patients admitted for the first time to a class Ⅲ level A hospital in Nanning as the research subjects. General information questionnaires， Mishel's Uncertainty in Illness Scale， Brief Illness Perception Questionnaire， and Perceived Social Support Scale were administered within 48 hours of admission. Latent profile analysis was employed to identify the latent classes of pre⁃treatment disease uncertainty in NPC patients. Based on the results of latent classes analysis， binary Logistic regression model was used to analyze the influencing factors for pre⁃treatment disease uncertainty in NPC patients. Results The total score of Mishel's Uncertainty in Illness Scale among 260 NPC patients before treatment was 74.68±11.60， with 90.8% of patients exhibiting moderate or higher levels of disease uncertainty. Through latent profile analysis， the pre⁃treatment disease uncertainty of NPC patients could be divided into two latent classes as follows: low disease uncertainty⁃complexity group and high disease uncertainty⁃complexity group. The results of binary Logistic regression analysis revealed that age， illness perception， educational level， and social support were the influencing factors for pre⁃treatment disease uncertainty in NPC patients (P<0.05). Conclusion NPC patients exhibit high levels of disease uncertainty before treatment， with distinct classification characteristics. Age， illness perception， educational level， and social support can influence the level of pre⁃treatment disease uncertainty in NPC patients.

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