Purpose <p>We compared the Oral Assessment Guide (OAG) and Oral Health Assessment Tool (OHAT) to determine which tool more accurately predicts prognosis in end-of-life patients with cancer.</p> Methods <p>This retrospective study included 116 end-of-life patients with cancer. Oral conditions were assessed using the OAG and OHAT. We performed receiver operating characteristic curve analysis with survival prognosis as the endpoint and compared the area under the curve (AUC). Hazard ratios (HRs) and 95% confidence intervals were calculated for the scores in unhealthy conditions using the health status score for each tool as a reference.</p> Results <p>The OAG had a significantly higher AUC at 14&#xa0;days (0.78 vs. 0.71, <i>p</i> = 0.02) and 21&#xa0;days (0.72 vs. 0.67, <i>p</i> = 0.03). After adjusting for age and performance status, lips showed significant differences on day 21 under mild/moderate condition (HR = 7.76) and on days 14 and 21 in the severe condition (HR = 38.57 and 38.57, respectively). Saliva showed significant differences on days 21 and 28 in the severe condition (HR = 5.70 and 3.80, respectively). Among the OAG-specific items, voice under severe condition on day 21 showed a significant difference (HR = 3.93), while no OHAT-specific items showed significant differences.</p> Conclusion <p>The OAG had significantly higher prognostic accuracy at 14 and 21&#xa0;days. The OAG-specific item voice may account for differences in diagnostic accuracy. The appropriate selection of an oral assessment tool enables the provision of patient-centered oral care, which is expected to alleviate discomfort and facilitate communication between patients and their families.</p>

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Oral health assessment of end-of-life patients with cancer: Evaluating the diagnostic accuracy of the oral assessment guide and oral health assessment tool in prognosis prediction

  • Mifumi Nakao,
  • Maiko Shimosato,
  • Naoki Sakane,
  • Takeshi Nakashima

摘要

Purpose

We compared the Oral Assessment Guide (OAG) and Oral Health Assessment Tool (OHAT) to determine which tool more accurately predicts prognosis in end-of-life patients with cancer.

Methods

This retrospective study included 116 end-of-life patients with cancer. Oral conditions were assessed using the OAG and OHAT. We performed receiver operating characteristic curve analysis with survival prognosis as the endpoint and compared the area under the curve (AUC). Hazard ratios (HRs) and 95% confidence intervals were calculated for the scores in unhealthy conditions using the health status score for each tool as a reference.

Results

The OAG had a significantly higher AUC at 14 days (0.78 vs. 0.71, p = 0.02) and 21 days (0.72 vs. 0.67, p = 0.03). After adjusting for age and performance status, lips showed significant differences on day 21 under mild/moderate condition (HR = 7.76) and on days 14 and 21 in the severe condition (HR = 38.57 and 38.57, respectively). Saliva showed significant differences on days 21 and 28 in the severe condition (HR = 5.70 and 3.80, respectively). Among the OAG-specific items, voice under severe condition on day 21 showed a significant difference (HR = 3.93), while no OHAT-specific items showed significant differences.

Conclusion

The OAG had significantly higher prognostic accuracy at 14 and 21 days. The OAG-specific item voice may account for differences in diagnostic accuracy. The appropriate selection of an oral assessment tool enables the provision of patient-centered oral care, which is expected to alleviate discomfort and facilitate communication between patients and their families.