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Simple Summary Oral cancer may strongly impair patients’ quality of life. Huge efforts have been made during recent decades in trying to improve the treatment outcomes in terms of patients’ survival, self-perception, and satisfaction. Consequently, the investigation into health-related quality of life (HRQOL) became an established and worldwide practice. Hundreds of studies tried to clarify which could be the most important variables that impact HRQOL in head and neck cancer patients. However, such a complex topic may be influenced by a multitude of interconnected aspects and several controversies were reported. In this study the current literature was reviewed to identify all those possible sources of bias that may be encountered in trying to correlate HRQOL to patient-specific or disease/treatment-specific aspects. As a result, a list of recommendations was reported to enhance the evidence of future studies. Abstract Background: health-related quality of life (HRQOL) represents a secondary endpoint of medical interventions in oncological patients. Our aim was to highlight potential sources of bias that could be encountered when evaluating HRQOL in oral cancer patients. Methods: this review followed PRISMA-ScR recommendations. Participants: patients treated for oral cancer. Concept: HRQOL assessed by EORTC QLQ-C30 and QLQ-H&N35/QLQ-H&N43. A critical appraisal of included studies was performed to evaluate the accuracy of data stratification with respect to HRQOL determinants. Results: overall, 30 studies met the inclusion criteria, totaling 1833 patients. In total, 8 sociodemographic (SDG) and 15 disease/treatment-specific (DT) HRQOL determinants (independent variables) were identified. The mean number of the independent variables was 6.1 (SD, 4.3)—5.0 (SD, 4.0) DT-related and 1.1 (SD, 1.8) SDG-related variables per article. None of the included papers considered all the identified determinants simultaneously. Conclusions: a substantial lack of evidence regarding HRQOL determinants was demonstrated. This strongly weakens the reliability of the reported findings due to the challenging presence of baseline confounding, selection, and omitted variable biases. The proposed approach recommends the use of further evaluation tools that gather more variables in a single score together with a selection of more homogeneous, reproducible, and comparable cohorts based on the identified baseline confounding.