Prognostic implication of dynamic platelet count in lung cancer patients with thrombocytosis: a retrospective analysis

Patient selection

We retrospectively analyzed 1,077 lung cancer patients treated at Changzhou Second People’s Hospital from January 2020 to December 2021. Elevated platelets were defined as counts ≥ 300*10⁹/L at any point during diagnosis or treatment, while counts consistently <300*10⁹/L were considered normal. Patients with acute infections, acute cardio-cerebrovascular diseases, receiving platelet-raising treatment, secondary lung malignancy, or missing data were excluded. We examined the time points of platelet elevation in 321 patients with elevated platelets and analyzed dynamic patterns of platelet count in 194 patients with elevated platelets, including 24 who had surgery with postoperative therapy and 170 receiving various treatment lines. Out of 321 patients with elevated platelets, we excluded 163 with missing first-line PFS data and those with small sample sizes due to factors like unknown metastatic sites, stage II disease, and specific cancer types (For details, see Fig. 1). This left 148 patients for prognosis analysis. Similarly, among patients with normal platelet counts, we excluded 183 with missing first-line PFS data and small sample sizes due to similar factors, resulting in 127 patients being included as the negative control group. The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Review Board of The Second People’s Hospital of Changzhou (protocol code [2023]KY314-01). Patient consent was waived due to the retrospective nature of the data collected.

Data collection and definition

In this study, we collected a comprehensive set of patient characteristics from medical records, including demographics (age and gender), tumor characteristics (pathological type, TNM stage, mutations, and programmed cell death ligand-1 (PDL1) expression), disease extent (site of metastasis), and treatment details (number of systemic therapy lines, treatment regimen, and PFS). The treatment encompass chemotherapy, chemo-based combination therapy (including radiotherapy, anti-angiogenic, and immunotherapy), targeted therapy, targeted-based combination therapy (including radiotherapy, anti-angiogenic, and chemotherapy), as well as immunotherapy with or without anti-angiogenic therapy. Additionally, the following parameters were also assessed, including time point of platelet elevation, dynamic patterns of platelet count throughout treatment (if available), MPV, PDW, lymphocyte count, neutrophil count, PLR, NLR, and D-dimer.

Based on the time points of platelet elevation during the treatment course, patients were categorized into the following groups: diagnosis, first-line treatment, progression after first-line treatment, post-operative period, adjuvant treatment, post-operative recurrence, second-line treatment, progression after second-line treatment, third-line or later treatment, and progression after third-line or later treatment.

Based on the dynamic patterns of platelet count following treatment, three patterns were identified: peak-type (where the elevated platelet count normalized after treatment), fluctuation-type (where the elevated platelet count normalized and then increased again later), and sustained-type (where the platelet count remained elevated throughout treatment).

Tumors were assessed at baseline, and efficacy was evaluated according to the criteria of RECIST 1.1. Progressive disease (PD) was defined as an increase of more than 20% in the sum of the longest diameters of all target lesions or the appearance of one or more new lesions. The primary endpoint was first-line PFS, which is defined as the duration from the initial of first-line treatment to the first occurrence of disease progression or death from any cause. The independent variables of the study include the time point of platelet elevation, dynamic patterns of platelet count, and platelet-related numerical parameters such as MPV, PDW, NLR, PLR and D-dimer. The covariates considered are clinical characteristics of lung cancer patients, including stage, histology, treatment and so on.

Statistical analysis

This study utilized several statistical techniques for data analysis. Baseline characteristics were assessed using the Wilcoxon rank-sum test for non-normally distributed continuous and ordinal variables, and the Pearson chi-square test for categorical variables. In the univariate analysis, Kaplan–Meier survival curves, along with log-rank tests, were initially employed to compare PFS between patients with elevated and normal platelets, serving as a primary descriptive and comparative measure of survival outcomes. Then both univariate and multivariate regression models were conducted to explore factors influencing patient survival outcomes. An initial exploration of potential variables affecting PFS was conducted using a univariate AFT model. Variables demonstrating statistical significance in the univariate AFT model were subsequently included in next-step multivariate analysis, wherein a multivariate AFT model was developed. In this multivariate AFT model analysis, a stepwise method was employed to establish the model and identify factors potentially associated with PFS.

In the subgroup analysis, we applied a consistent methodology to patients with elevated platelets to investigate factors associated with PFS. Initially, a univariate AFT model was utilized to identify factors potentially related to PFS. Factors demonstrating statistical significance in the univariate AFT model were subsequently included in a multivariate AFT model analysis. Those factors that remained statistically significant in the multivariate AFT model were ultimately identified as influential determinants of PFS in patients with elevated platelets. All statistical analyses were performed using the R statistical programming language (version 4.3.2), and a p-value of less than 0.05 was statistically significant.

Baseline characteristics and prognosis of lung cancer patients

Baseline characteristics of patients with elevated and normal platelets are presented in Table 1. There were no significant differences between the two groups in sex, age at diagnosis, lymphocyte count, NLR, histology, clinical stage, and treatment. Data were based on existing records, and not all patients were tested for mutations and PD-L1 expression, so these variables weren’t statistically analyzed. The elevated platelet group had a higher proportion of ALK mutations (6% vs. 0.7%, respectively), but due to the small sample sizes this requires further confirmation. Metastatic sites were similar in both groups. Compared to patients with normal platelets, those with elevated platelets had significantly lower MPV and PDW, as well as higher neutrophils, PLR, and D-dimer. The follow-up time in the elevated group was significantly shorter, indicating that earlier disease progression was observed.

We initially analyzed prognostic factors in lung cancer patients. Kaplan–Meier survival curves showed that histology and treatment were significantly associated with first-line PFS (Fig. S1). The PFS was significantly lower in males than females, potentially due to a higher mutation prevalence in female patients (65% vs. 35%, respectively), and targeted therapy, both mono- and combination regimens, were associated with superior PFS outcomes. Univariate analysis revealed that in addition to sex, histology, and treatment, elevated platelets and D-dimer were closely related to PFS (Table S1). Further multivariate AFT model analysis confirmed that elevated platelets, along with D-dimer and treatment, were correlated with PFS in lung cancer patients (Table S2).

The distribution of the time point of platelet elevation and the dynamic pattern of platelet count in patients with thrombocytosis

As shown in the flow chart (Fig. 1), 68 patients were first excluded and a total of 1,009 patients with lung cancer were documented. Of these, 321 patients were included in the elevated platelet group, representing 31.8% of the total included patients. Most patients experienced an increase in platelet count at the time of diagnosis (50.47%), followed by the first-line treatment period (20.56%) (Fig. 2). Among the 194 patients who completed treatment and post-treatment follow-up, the peak-type pattern was the most common (46.91%), followed by the fluctuation-type (42.78%), and the least prevalent was the sustained-type (10.31%) (Fig. 3).

Prognostic factors for lung cancer patients with thrombocytosis

Based on the result that elevated platelets were correlated with first-line PFS in lung cancer patients, we further investigated the prognostic factors for lung cancer patients with thrombocytosis. As shown in Fig. 4, the time point of platelet elevation, whether at diagnosis or during first-line treatment, did not associated with first-line PFS (p = 0.81). However, dynamic patterns of platelet count showed a significant correlation with first-line PFS (p < 0.0001). Univariate analysis revealed the same general results (Table 2). While there were significant differences in neutrophil and PLR between patients with elevated and normal platelets, these variables did not show a notable association with PFS in patients with elevated platelets. Patients with elevated platelets exhibited lower MPV and PDW and higher D-dimer levels, all of which were significantly associated with first-line PFS.

To further investigate the influence of platelet-related factors, a multivariate analysis was conducted (Table 3). The dynamic pattern of platelet count remained strongly associated with first-line PFS. Compared to patients with peak-type, patients with sustained-type had the worst PFS (β =  − 1.291, p < 0.001). Although patients with fluctuation-type exhibited worse PFS (β =  − 0.358, p = 0.054), the difference was not statistically significant. Among numerical variables, MPV was positively correlated with PFS, while D-dimer was negatively correlated.