Evaluation of Preoperative Hematologic Markers as Prognostic Factors and Establishment of Novel Risk Stratification in Resected pN0 Non-Small-Cell Lung Cancer

<div><p>Background</p><p>The aims of this study were to investigate whether the preoperative hematologic markers, the neutrophil-lymphocyte ratio (NLR) or the platelet-lymphocyte ratio (PLR) were prognostic indicators and to develop a novel risk stratification model in pN0 non-small-cell lung cancer (NSCLC).</p><p>Methods</p><p>We performed a retrospective analysis of 400 consecutive pN0 NSCLC patients. Prognostic values were evaluated by Cox proportional hazard model analyses and patients were stratified according to relative risks for patients’ survival.</p><p>Results</p><p>During the follow-up, 117 patients had cancer recurrence, and 86 patients died. In univariate analysis, age, gender, smoke status and tumor size as well as WBC, NEU, LYM, PLR and NLR were significantly associated with patients’ prognosis. In multivariate analysis, age, tumor size and NLR were independent predictors for patients’ overall survival (P = 0.024, 0.001, and 0.002 respectively). PLR didn’t associated with patients’ survival in multivariate analysis. Patients were stratified into 3 risk groups and the differences among the groups were significant according to disease free survival and overall survival (P = 0.000 and 0.000 respectively).</p><p>Conclusions</p><p>We confirmed that NLR other than PLR was an independent prognostic factor. Combination of NLR, age and tumor size could stratify pN0 NSCLC patients into 3 risk groups and enabled us to develop a novel risk stratification model.</p></div

Distribution of clinical characteristics stratified by pretreatment NLR or PLR.

<p>Distribution of clinical characteristics stratified by pretreatment NLR or PLR.</p

Univariate analysis of clinical characteristics' affect on 3 years survival.

&<p>This variable just included the resected NSCLC cases;</p>▽<p>These cases came from the follow-up of resected NSCLC patients who were not detected bone metastases at primary care;</p><p>LN: Lymph node.</p

Kaplan-Meier estimates according to low, intermediate and high risk groups on DFS (a) and OS (b).

<p>Kaplan-Meier estimates according to low, intermediate and high risk groups on DFS (a) and OS (b).</p

Relations of clinical and pathological characteristics and Blood Calcium levels in NSCLC patients.

§<p>These variables is not included, because it is too less and not enough for statistics analysis;</p>&<p>This variable just included the resected NSCLC cases;</p>▽<p>These cases came from the follow-up of resected NSCLC patients who were not detected bone metastases at primary care;</p><p>LN: Lymph node;</p>a<p>Compare of never smokers to smoking index≧400;</p>b<p>Compare of well differentiation to moderately and poorly differentiation;</p>c<p>Compare of adenomas with squamous lung carcinomas, because others is too less and have special features.</p

Multivariate analysis of clinical characteristics affect on 3-year survival using COX regression model.

△<p>These variables were selected from the variables that have effects on 3-year survival using univariate analysis;</p><p>HR: Hazard Ratio; CI: Confidence Interval; LN: Lymph node.</p

The Kaplan-Meier survival curve of NSCLC patients who underwent radical resection (n = 572).

<p>It is analyzed using Kaplan-Meier survival model, including 108 cases with blood calcium <2.2, and 464 cases with 2.2< = calcium< = 2.6. Log-rank comparisons revealed that blood calcium decrease(<2.2 µM) was associated with shorter survival (Log-rank; χ² = 26.172, <i>P</i><0.001).</p

The changes of Blood electrolytes in 1084 cases with NSCLC.

<p>NSCLC: non small cell lung cancer;</p>§<p>These cases is not included, because it is too less and not enough for statistic analyses;</p>#<p>the incidence of calcium decrease compare with others blood electrolytes, including magnesium, potassium, sodium and chlorine.</p

Kaplan-Meier estimates according to categorical age, tumor size, NLR and PLR on DFS (a, b, c, d) and OS (e, f, g, h).

<p>Kaplan-Meier estimates according to categorical age, tumor size, NLR and PLR on DFS (a, b, c, d) and OS (e, f, g, h).</p

Multivariate proportional hazards (Cox) regression analyses according to DFS and OS.

<p>Multivariate proportional hazards (Cox) regression analyses according to DFS and OS.</p