Diagnostic delay in lung cancer in Morocco: A 4-year retrospective study

Background: Lung cancer is a major cause of morbidity and mortality worldwide. The diagnosis of lung cancer is complex and can be easily missed or delayed. The aim of this study is to describe the delay in diagnosis and evaluate the factors associated with diagnosis delay. Methods: All patients diagnosed with primary lung cancer at Moulay Youssef University hospital in Rabat from January 2014 to December 2017 were investigated retrospectively. Data relating to patient characteristics, tumor characteristics, and all dates of visits and investigations were collected. Multivariate linear regression analysis was used to identify risk factors linked to delayed diagnosis. Results: A total of 81 patients were included (81,5% were men). Around 85.2% of patients presented lung-related symptoms. Cough and dyspnea were the most common symptoms. The median time of the patient presentation was 75 days (interquartile interval (IQI) = 30-150 days), patient referral time was 08 days (IQI = 02-14 days), diagnosis time was 21 days (IQI = 14-22 days). In multivariate analysis, a higher age (p = 0.044) and weight loss (p = 0.038) were associated with an increased presentation patient time. Asthma (p = 0.004) and chronic obstructive pulmonary disease (COPD) (p = 0.040) were significantly associated with delayed referral time. Diagnosis time was longer in patients with non-suspected Chest-X ray (p = 0.045) and earlier in patients diagnosed with computed tomography-guided biopsy (p = 0.030). Conclusion: Intervals of diagnosis were significantly delayed and highly affected by patients and diagnostic times. Thus, the results emphasize the extreme need to develop efficient strategies to improve lung cancer diagnosis intervals.

Automated summary

This study investigated the delay in diagnosis of lung cancer and evaluated the factors associated with this delay. The results showed that the intervals of diagnosis were significantly delayed and highly affected by patients and diagnostic times. Therefore, it is crucial to develop efficient strategies to improve the diagnosis intervals of lung cancer.