Frontiers in pharmacology · 2026
Clinical, laboratory, and medication-related factors associated with in-hospital mortality among oncology patients at a tertiary hospital in Saudi Arabia.
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Alafnan Ahmed, Alorainan Meshal M, Alanazi Sanad M, Algharbi Salman F, Alshammari Faisal R, Alghaslan Ammar, Saleem Hammad, Alghamdi Saleh, Shaikh Mohd Farooq, Anwar Sirajudheen
Аннотация
BACKGROUND: Oncology inpatients face physiological decline alongside complex pharmacology, yet clinical mortality predictors and drug-related risks remain understudied in Middle Eastern populations. This study identified independent predictors of in-hospital mortality and characterized potential drug-drug interactions (pDDIs) among hospitalized cancer patients in Saudi Arabia.
METHODS: This retrospective cohort study evaluated 401 adult oncology inpatients admitted to a tertiary care center in Hail, Saudi Arabia (2020-2022). Demographics, clinical parameters, and medication profiles were extracted from medical records. Bivariate correlations were assessed using point-biserial ( r p b ) and phi ( ϕ ) coefficients. Independent mortality predictors were identified via multivariable binary logistic regression, and biomarker discrimination was evaluated using receiver operating characteristic (ROC) curves. Potential DDIs were screened using Drugs.com.
RESULTS: The cohort was predominantly female (67.6%) and Saudi (85.0%), with solid malignancies accounting for 94.3% of cases. In-hospital mortality was 25.2% ( n = 101 / 401 ). Bivariate correlations demonstrated significant associations with mortality across clinical parameters, including mechanical ventilation requirements ( ϕ = 0.118 , p = 0.018 ). Multivariable regression identified four independent physiological predictors of mortality: renal failure ( aOR = 44.29 , 95 % CI : 1.07 - 1836.31 ), baseline albumin aOR = 0.71 per g / L , 95 % CI : 0.55 - 0.91 , serum creatinine ( aOR = 1.02 per μ mol / L , 95 % CI : 1.001 - 1.04 ), and oxygen saturation ( aOR = 0.68 per % , 95 % CI : 0.50 - 0.93 ). Serum albumin showed high individual discrimination ( AUC = 0.920 ), while the combined multivariable model achieved an AUC of 0.953. Pharmacological screening revealed near-universal interaction prevalence: 98.6% of 2,148 prescriptions contained a pDDI flag (54.9% severe), and 96.5% of patients had ≥ 1 severe pDDI flag.
CONCLUSION: In-hospital mortality is strongly driven by acute organ dysfunction and physiological decline rather than database-flagged interactions alone. However, the high prevalence of severe pDDI flags highlights a critical need to integrate structured clinical pharmacy reviews into oncology admission protocols. Targeted medication safety interventions should focus on avoiding nephrotoxic combinations and establishing pre-therapeutic pharmacogenetic screening to mitigate potential iatrogenic risks.
METHODS: This retrospective cohort study evaluated 401 adult oncology inpatients admitted to a tertiary care center in Hail, Saudi Arabia (2020-2022). Demographics, clinical parameters, and medication profiles were extracted from medical records. Bivariate correlations were assessed using point-biserial ( r p b ) and phi ( ϕ ) coefficients. Independent mortality predictors were identified via multivariable binary logistic regression, and biomarker discrimination was evaluated using receiver operating characteristic (ROC) curves. Potential DDIs were screened using Drugs.com.
RESULTS: The cohort was predominantly female (67.6%) and Saudi (85.0%), with solid malignancies accounting for 94.3% of cases. In-hospital mortality was 25.2% ( n = 101 / 401 ). Bivariate correlations demonstrated significant associations with mortality across clinical parameters, including mechanical ventilation requirements ( ϕ = 0.118 , p = 0.018 ). Multivariable regression identified four independent physiological predictors of mortality: renal failure ( aOR = 44.29 , 95 % CI : 1.07 - 1836.31 ), baseline albumin aOR = 0.71 per g / L , 95 % CI : 0.55 - 0.91 , serum creatinine ( aOR = 1.02 per μ mol / L , 95 % CI : 1.001 - 1.04 ), and oxygen saturation ( aOR = 0.68 per % , 95 % CI : 0.50 - 0.93 ). Serum albumin showed high individual discrimination ( AUC = 0.920 ), while the combined multivariable model achieved an AUC of 0.953. Pharmacological screening revealed near-universal interaction prevalence: 98.6% of 2,148 prescriptions contained a pDDI flag (54.9% severe), and 96.5% of patients had ≥ 1 severe pDDI flag.
CONCLUSION: In-hospital mortality is strongly driven by acute organ dysfunction and physiological decline rather than database-flagged interactions alone. However, the high prevalence of severe pDDI flags highlights a critical need to integrate structured clinical pharmacy reviews into oncology admission protocols. Targeted medication safety interventions should focus on avoiding nephrotoxic combinations and establishing pre-therapeutic pharmacogenetic screening to mitigate potential iatrogenic risks.