This study analyzed the risk factors and clinical characteristics of patients with LC-PTB and classified the study population from various perspectives. We not only identified the main factors influencing clinical manifestations in these patients but also assessed the risk factors affecting the efficacy of tuberculosis therapy across different groups. We understand the importance of personalized treatment in clinical practice. It is essential to develop individualized treatment strategies based on specific circumstances. The presence of preexisting APTB and advanced LC stages may increase the risk of failure of anti-TB therapy, complicating patient management. This suggests that clinicians should pay extra attention to these factors and adopt more proactive and comprehensive management approaches when treating such patients.
Analysis of the clinical characteristics of patients with LC-PTB and its subgroups, LC-APTB and LC-IPTB, revealed key findings. Firstly, demographic characteristics showed that the median age of the LC-PTB group was 64 years, with a predominance of males and a widespread history of smoking, consistent with the literature suggesting that lung cancer with concurrent tuberculosis is common in older males who smoke12–14. Additionally, we found that the median age of LC-IPTB patients was slightly greater than that of LC-APTB patients, suggesting15 that younger LC patients might be more prone to active pulmonary tuberculosis. Clinically, NSCLC was the dominant type of lung cancer in both subgroups, aligning with the global pathological distribution of LC patients. Radiological analysis indicated that 64.4% (259/402) of patients had PTB lesions colocated with LC primary lesions on the same side, particularly in the LC-APTB group, which could be related to 16local immunosuppression, changes in the microenvironment, pathological damage and repair processes, and reactivation of dormant tubercle bacilli. Lesions and tumors in pulmonary tuberculosis patients are most commonly found in the same lobe or lung (53%) but on different lobes on the same side (25%)17. Additionally, cavitation was significantly more prevalent in the LC-IPTB group than in the LC-APTB group, possibly reflecting18,19 the long-term impact of TB on the pathways leading to lung cancer development. This observation underscores the importance of close monitoring of patients with a history of IPTB.
From the perspective of mycobacterial status classification, the B−PTB group exhibited more contralateral lesions than did the B+PTB group, while the LC-B+PTB group displayed more cavitary lesions, potentially related to a greater bacterial load and virulence and a lower immune status in bacterium-positive pulmonary tuberculosis20. The treatment success rate for LC-ATPB was only 67.4%, significantly lower than the 2020 success rate for TB in China5. These findings are at odds with those of Su S and other scholars, who contend that simultaneous TB and cancer treatments do not compromise efficacy21–23. This suggests that the coexistence of LC could hinder the effectiveness of TB treatment. Critical factors influencing treatment success may include treatment interruptions, adjustments in therapeutic protocols, and side effects such as liver damage or drug intolerance leading to treatment discontinuation. Moreover, challenges such as the prevalence of drug-resistant TB and the complexities involved in diagnosing and treating latent TB infection in LC patients may exacerbate this situation 24,25. Additionally, compared to that in the TB group, the mortality rate during anti-TB therapy in the LC group was notably high, reaching 24.7%. In other words, Shieh et al 26 revealed a greater risk of death in patients with LC-PTB. This concurrence with our study may stem from compromised immune clearance mechanisms against Mtb and sustained pulmonary inflammatory responses, potentially reducing survival rates27. Notably, the B-PTB subgroup demonstrated a greater success rate of anti-TB treatment than did the B + PTB subgroup. The literature suggests that patients who achieve negative sputum smears within two months of treatment initiation have nearly triple the odds of TB cure, possibly due to reduced bacterial burden28,29.
Logistic regression analysis was employed to evaluate factors influencing the efficacy of tuberculosis therapy in LC-APTB patients. The study suggested that a history of APTB and advanced-stage LC could increase the risk of treatment failure. Early-stage LC is often difficult to distinguish from short-term TB lesions, which can delay LC staging and timely surgical intervention, adversely affecting patient survival and prognosis30. Lee et al 31 showed that patients with LC diagnosis and concurrent APTB are more likely to have advanced LC, which may involve immune factors and thus affect the outcome of anti-TB therapy. Moreover, the presence of preexisting PTB has been shown to increase lung cancer mortality32, thereby affecting treatment outcomes.
This study has several limitations. Firstly, the sample size and regional restrictions may affect the generalizability of the research results, limiting their applicability to a broader population. Secondly, as a single-center retrospective study, data collection relies on historical medical records, which may introduce information bias and selection bias, thus affecting the reliability of the results. Finally, the study may not have adequately controlled for all relevant confounding variables, such as the presence of drug-resistant TB, which could influence the study's conclusions. The study design itself also has limitations, particularly in determining causal relationships and observing long-term disease progression.
To improve the study, the following measures can be taken. The sample size should be increased, and multicenter collaborative research across different regions should be conducted to enhance the representativeness and generalizability of the results, thereby reducing regional bias. A prospective study design should be used to more effectively track the natural progression of the disease and the effects of treatment. Pure control studies were selected to provide higher levels of evidence to determine causal relationships. For patient survival prognosis, data on overall survival and progression-free survival are included to enable a more comprehensive evaluation of prognosis and the effectiveness of treatment strategies.