Prognostic Value of a Nomogram Based on the Dynamic Albumin-to-Alkaline Phosphatase Ratio for Patients with Extensive-Stage Small-Cell Lung Cancer

Development of a novel nomogram for patients with SCLC and comparison with other models

BACKGROUND

Though several nomograms have been established to predict the survival probability of patients with small-cell lung cancer (SCLC), none involved enough variables. This study aimed to construct a novel prognostic nomogram and compare its performance with other models.

METHODS

Seven hundred twenty-two patients were pathologically diagnosed with SCLC in Shanxi Province Cancer Hospital, Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences, Cancer Hospital Affiliated to Shanxi Medical University from January 2016 to December 2018. We input Forty-one factors by reviewing the medical records. The nomogram was constructed based on the variables identified by univariate and multivariate analyses in the training set and validated in the validation set. Then we compared the performance of the models in terms of discrimination, calibration, and clinical net benefit.

RESULTS

There were eight variables involved in the nomogram: gender, monocyte (MON), neuron-specific enolase (NSE), cytokeratin 19 fragments (Cyfra211), M stage, radiotherapy (RT), chemotherapy cycles (CT cycles), and prophylactic cranial irradiation (PCI). The calibration curve showed a good correlation between the nomogram prediction and actual observation for overall survival (OS). The area under the curve (AUC) of the nomogram was higher, and the Integrated Brier score (IBS) was lower than other models, indicating a more accurate prediction. Decision curve analysis (DCA) showed a significant improvement in the clinical net benefit compared to the other models.

CONCLUSIONS

We constructed a novel nomogram to predict OS for patients with SCLC using more comprehensive and objective variables. It performed better than existing models and would assist clinicians in individually estimating risk and making a therapeutic regimen.

Risk stratification and overall survival prediction in extensive stage small cell lung cancer after chemotherapy with immunotherapy based on CT radiomics

The prognosis of extensive-stage small cell lung cancer is usually poor. In this study, a combined model based on pre-treatment CT radiomics and clinical features was constructed to predict the OS of extensive-stage small cell lung cancer after chemotherapy with immunotherapy.Clinical data of 111 patients with extensive stage small-cell lung cancer who received first-line immunotherapy combined with chemotherapy in our hospital from December 2019 to December 2021 were retrospectively collected. Finally, 93 patients were selected for inclusion in the study, and CT images were obtained through PACS system before treatment. All patients were randomly divided into a training set (n = 66) and a validation set (n = 27). Images were imported into ITK-SNAP to outline areas of interest, and Python software was used to extract radiomics features. A total of 1781 radiomics features were extracted from each patient's images. The feature dimensions were reduced by MRMR and LASSO methods, and the radiomics features with the greatest predictive value were screened. The weight coefficient of radiomics features was calculated, and the linear combination of the feature parameters and the weight coefficient was used to calculate Radscore. Univariate cox regression analysis was used to screen out the factors significantly associated with prognosis from the radiomics and clinical features, and multivariate cox regression analysis was performed to establish the prognosis prediction model of extensive stage small cell lung cancer. The degree of metastases was selected as a significant clinical prognostic factor by univariate cox regression analysis. Seven radiomics features with significance were selected by LASSO-COX regression analysis, and the Radscore was calculated according to the coefficient of the radiomics features. An alignment diagram survival prediction model was constructed by combining Radscore with the number of metastatic lesions. The study population was stratified into those who survived less than 11 months, and those with a greater than 11 month survival. The C-index was 0.722 (se = 0.044) and 0.68(se = 0.074) in the training and the validation sets, respectively. The Log_rank test results of the combination model were as follows: training set: p < 0.0001, validation set: p = 0.00042. In this study, a combined model based on radiomics and clinical features could predict OS in patients with extensive stage small cell lung cancer after chemotherapy with immunotherapy, which could help guide clinical treatment strategies.

Predicting pathological complete response after neoadjuvant chemotherapy in breast cancer by clinicopathological indicators and ultrasound parameters using a nomogram

The study explored the impact of pretreatment serum albumin-to-alkaline phosphatase ratio (AAPR) and changes in tumor blood supply on pathological complete response (pCR) in breast cancer (BC) patients following neoadjuvant chemotherapy (NACT). Additionally, a nomogram for predicting pCR was established and validated. The study included BC patients undergoing NACT at Yongchuan Hospital of Chongqing Medical University from January 2019 to October 2023. We analyzed the correlation between pCR and clinicopathological factors, as well as tumor ultrasound features, using chi-square or Fisher's exact test. We developed and validated a nomogram predicting pCR based on regression analysis results. The study included 176 BC patients. Logistic regression analysis identified AAPR [odds ratio (OR) 2.616, 95% confidence interval (CI) 1.140-5.998, P = 0.023], changes in tumor blood supply after two NACT cycles (OR 2.247, 95%CI 1.071-4.716, P = 0.032), tumor histological grade (OR 3.843, 95%CI 1.286-10.659, P = 0.010), and HER2 status (OR 2.776, 95%CI 1.057-7.240, P = 0.038) as independent predictors of pCR after NACT. The nomogram, based on AAPR, changes in tumor blood supply after two NACT cycles, tumor histological grade, and HER2 status, demonstrated a good predictive capability.

Clinical role of pretreatment albumin-to-alkaline phosphatase ratio in lung cancer: a meta-analysis

The association between pretreatment albumin-to-alkaline phosphatase ratio (AAPR) and clinicopathological parameters and prognosis in lung cancer is unclear. The study aimed to identify the clinical role of pretreatment AAPR among lung cancer patients. Several databases were searched for relevant studies. The primary outcome and secondary outcome were long-term survival including the overall survival (OS) and progression-free survival (PFS) and clinicopathological characteristics, respectively. The hazard ratios (HRs) and relative risks (RRs) with 95% confidence intervals (CIs) were combined. A total of 11 publications involving 10,589 participants were included in this meta-analysis. The pooled results manifested that a lower pretreatment AAPR predicted poorer OS (HR = 0.65, 95% CI 0.59-0.71, P < 0.001) and PFS (HR = 0.68, 95% CI 0.59-0.78, P < 0.001). Furthermore, subgroup analysis for the OS and PFS based on the pathological type and treatment showed similar results and pretreatment AAPR was significantly associated with worse prognosis. Besides, pretreatment AAPR was significantly associated with male (RR = 1.08, 95% CI 1.03-1.13, P < 0.001), poor differentiation (RR = 1.33, 95% CI 1.03-1.73, P = 0.029), advanced T stage (RR = 1.25, 95% CI 1.03-1.52, P = 0.026), N stage (RR = 1.34, 95% CI 1.15-1.55, P < 0.001) and TNM stage (RR = 1.14, 95% CI 1.06-1.223, P < 0.001). Therefore, pretreatment AAPR is significantly related to prognosis and tumor stage in lung cancer and patients with a lower pretreatment AAPR are more likely to experience poor survival and advanced tumor stage.

The impact of serum albumin-to-alkaline phosphatase ratio in cervical cancer patients treated with definitive chemoradiotherapy

We retrospectively analysed the prognostic significance of serum albumin, alkaline phosphatase (ALP) and albumin to ALP ratio (AAPR) and other prognostic factors affecting the overall survival (OS) and progression-free survival (PFS) in 200 cervical cancer patients treated with definitive chemoradiotherapy (CRT). The prognostic factors for OS and DFS, in addition to the predictive factors of albumin, ALP and AAPR, were investigated. Older age, lymph node metastasis, non-complete response (CR) to treatment and low serum albumin levels emerged as predictors of poor OS and PFS in multivariate analysis. However, with a cut-off value of 0.51, AAPR was not a significant prognostic factor of survival in multivariable analysis. There were no significant differences in clinicopathological factors between patients with low and high AAPR, except for lymph node metastasis, where lymph node metastasis rate was significantly higher in patients with a low AAPR compared to those with a high AAPR. Patients with CR had a significantly higher serum albumin level and AAPR compared to patients without CR. The pre-treatment serum albumin level was independent predictive for survival; therefore, it could be a suitable biomarker to guide systemic therapy and predict patient outcomes. Impact StatementWhat is already known on this subject? Two major determinants of tumour progression are nutritional status and inflammation. The albumin-to-alkaline phosphatase ratio (AAPR), which was originally proposed as a marker for nutritional status and immune response, was recently discovered to be a prognostic factor for various cancer types. However, its utility in the treatment of cervical cancer has not been established.What do the results of this study add? Low serum albumin levels were associated with a significantly shorter OS and PFS in cervical cancer patients treated definitively with CRT. AAPR, on the other hand, was not a significant prognostic factor for survival with a cut-off value of 0.51. Regional lymph node metastasis was significantly more common in patients with a low AAPR than in those with a high AAPR.What are the implications of these findings for clinical practice and/or further research? Patients with multiple clinicopathological risk factors and low serum albumin levels had an increased risk of disease recurrence and a poorer prognosis, highlighting the importance of additional adjuvant treatment strategies in these patients. Due to the preliminary nature of our findings, additional research is required to corroborate them.

External Application of a Nomogram to Predict Survival and Benefit of Peripheral Blood Inflammatory Indexes in Limited-Stage Small Cell Lung Cancer

Background

Qi et al. recently proposed a nomogram to reveal the prognostic value of peripheral blood inflammatory indexes (named Risk) and predict overall survival (OS) in limited-stage small cell lung cancer (LS-SCLC). However, it hasn’t undergone external application so far. This study aimed to verify the role of Risk as a prognostic variable of OS and apply the nomogram externally.

Methods

We used a retrospective analysis of clinical data of 254 patients diagnosed as LS-SCLC in Shanxi Cancer Hospital from January 2015 to December 2018 to apply Qi’s nomogram externally. We also performed subgroup analysis to explore the predictive value of Risk. The model was evaluated in terms of discrimination (the area under the ROC curve (AUC ROC) and calibration (calibration plots).

Results

The prognosis of patients with low-Risk was significantly better than those with high-Risk in our cohort (p<0.01). The AUC of 1-, 2-, and 3-year OS was 0.644, 0.666, and 0.635, respectively. The calibration curve showed a nearly ideal calibration-slope of 1-, 2-, and 3-year OS (1.00 (0.41-1.59), 1.00 (0.54-1.46) and 1.00 (0.43-1.57), respectively).

Conclusion

The external application of nomogram added Risk for predicting OS in LS-SCLC patients showed a moderate-to-good performance using a cohort with different case-mix characteristics. The external application confirmed the predictive value of Risk and the usefulness of the nomogram for the prediction of OS.

Prognostic Value of Albumin-to-Alkaline Phosphatase Ratio for EGFR-Mutated Advanced Non-Small-Cell Lung Cancer Patients Treated with First-Line EGFR-TKIs: A Large Population-Based Study and Literature Review

Background

Resistance inevitably develops in epidermal growth factor receptor (EGFR)-mutated advanced non-small-cell lung cancer (NSCLC) patients after treatment of EGFR tyrosine kinase inhibitors (EGFR-TKIs). The albumin-to-alkaline phosphatase ratio (AAPR), a novel index, has been reported to be associated with survival in various cancers. In this study, we explored the prognostic value of AAPR in EGFR-mutated advanced NSCLC patients treated with first-line EGFR-TKIs.

Methods

The clinical and pretreatment laboratory data were retrospectively extracted from hospital medical system. The Log-rank and Kaplan–Meier analyses were adopted to detect differences in survival between groups. Univariate and multivariate Cox’s proportional hazard regression models were applied to assess the prognostic value of AAPR for progression-free survival (PFS) and overall survival (OS).

Results

Totally, 598 EGFR-mutated NSCLC patients with stage IIIB-IV were enrolled into this study. The median age of all patients was 60 years, and 56.9% were women. About 97% patients had common EGFR gene mutations of deletions in exon 19 (19 del) or a point mutation in exon 21 (L858R). Using receiver operating characteristic (ROC) curve analysis and the Youden index, the optimal cut-off value of pretreatment AAPR was 0.47. Patients with high AAPR achieved longer median PFS and OS than patients with low AAPR (14.0 months vs 10.4 months, P<0.01; 58.2 months vs 36.7 months, P<0.001, respectively). The multivariate analysis by Cox’s proportional hazards regression model demonstrated that AAPR was an independent prognostic factor for both PFS (HR: 0.813, 95% CI: 0.673–0.984, P=0.033) and OS (HR: 0.629, 95% CI: 0.476–0.830, P=0.001).

Conclusion

Pretreatment AAPR, measured as part of routine blood biochemical test, may be a reliable prognostic indicator in EGFR-mutated advanced NSCLC patients treated with first-line first-generation EGFR-TKIs.

Pretreatment Albumin-to-Alkaline Phosphatase Ratio Is a Prognostic Marker in Lung Cancer Patients: A Registry-Based Study of 7077 Lung Cancer Patients

Simple Summary

Since the albumin-to-alkaline phosphatase ratio (AAPR) has shown promising prognostic prediction in cancer patients, the prognostic value of the AAPR was evaluated in a large cohort of 7077 lung cancer patients. We combined patient data from the Danish Lung Cancer Registry and the clinical laboratory information system (LABKA) and showed that a low AAPR was independently associated with an inferior median overall survival in non-small cell lung cancer patients and small cell lung cancer patients. Furthermore, data indicated a level-dependent correlation between the AAPR and survival and that the AAPR added additional prognostic value to the already well-established prognostic markers in lung cancer. Therefore, if our findings are validated in the future, the AAPR should be incorporated as a factor in the general prognostication of lung cancer patients.

Abstract

The albumin-to-alkaline phosphatase ratio (AAPR) is a novel promising prognostic marker in cancer patients. However, the evidence for its significance in lung cancer is scarce. Therefore, we assessed the prognostic value of the AAPR in a large cohort of lung cancer patients. Data on lung cancer patients diagnosed from January 2009 to June 2018 were extracted from the Danish Lung Cancer Registry and combined with data on the pretreatment serum AAPR level extracted from the clinical laboratory information system (LABKA). AAPR tertiles were applied as cutoffs. Cox proportional hazard models assessed the prognostic value of the AAPR. In total, 5978 non-small cell lung cancer (NSCLC) patients and 1099 small cell lung cancer (SCLC) patients were included. Decreasing AAPR level was significantly associated with declining median overall survival (OS) in NSCLC patients (medium vs. low AAPR, adjusted HR = 0.73 (95% confidence interval (CI) 0.68–0.79); high vs. low AAPR, adjusted HR = 0.68 (95% CI 0.62–0.73)) and in SCLC patients (medium vs. low AAPR, adjusted HR = 0.62 (95% CI 0.52–0.74); high vs. low, adjusted HR = 0.59 (95% CI 0.50–0.70)). In conclusion, the AAPR was an independent prognostic factor in NSCLC and SCLC patients. The correlation seems to be level dependent, with reducing survival found to be associated with decreasing AAPR level.

Construction and Validation of a Serum Albumin-to-Alkaline Phosphatase Ratio-Based Nomogram for Predicting Pathological Complete Response in Breast Cancer

Background

Breast cancer patients who achieve pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) have favorable outcomes. Reliable predictors for pCR help to identify patients who will benefit most from NAC. The pretreatment serum albumin-to-alkaline phosphatase ratio (AAPR) has been shown to be a prognostic predictor in several malignancies, but its predictive value for pCR in breast cancer is still unknown. This study aims to investigate the predictive role of AAPR in breast cancer patients and develop an AAPR-based nomogram for pCR rate prediction.

Methods

A total of 780 patients who received anthracycline and taxane-based NAC from January 2012 to March 2018 were retrospectively analyzed. Univariate and multivariate analyses were performed to assess the predictive value of AAPR and other clinicopathological factors. A nomogram was developed and calibrated based on multivariate logistic regression. A validation cohort of 234 patients was utilized to further validate the predictive performance of the model. The C-index, calibration plots and decision curve analysis (DCA) were used to evaluate the discrimination, calibration and clinical value of the model.

Results

Patients with a lower AAPR (<0.583) had a significantly reduced pCR rate (OR 2.228, 95% CI 1.246-3.986, p=0.007). Tumor size, clinical nodal status, histological grade, PR, Ki67 and AAPR were identified as independent predictors and included in the final model. The nomogram was used as a graphical representation of the model. The nomogram had satisfactory calibration and discrimination in both the training cohort and validation cohort (the C-index was 0.792 in the training cohort and 0.790 in the validation cohort). Furthermore, DCA indicated a clinical net benefit from the nomogram.

Conclusions

Pretreatment serum AAPR is a potentially valuable predictor for pCR in breast cancer patients who receive NAC. The AAPR-based nomogram is a noninvasive tool with favorable predictive accuracy for pCR, which helps to make individualized treatment strategy decisions.

Computerized Assessment of the Tumor-stromal Ratio and Proposal of a Novel Nomogram for Predicting Survival in Invasive Breast Cancer

Background: Various studies have verified the prognostic significance of the tumor-stromal ratio (TSR) in several types of carcinomas using manually assessed H&E stained histologic sections. This study aimed to establish a computerized method to assess the TSR in invasive breast cancer (BC) using immunohistochemistry (IHC)-stained tissue microarrays (TMAs), and integrate the TSR into a novel nomogram for predicting survival.

Methods: IHC-staining of cytokeratin (CK) was performed in 7 prepared TMAs containing 240 patients with 480 invasive BC specimens. The ratio of tumor areas and stromal areas was determined by the computerized method, and categorized as stroma-low and stroma-high groups using the X-tile software. The prognostic value of the TSR at 5-year disease free survival (5-DFS) in each subgroup was analyzed. Univariate and multivariate analyses were performed and a novel nomogram for predicting survival in invasive breast cancer was established and assessed.

Results: The newly developed computerized method could accurately recognize CK-labeled tumor areas and non-labeled stromal areas, and automatically calculate the TSR. Stroma-low and stroma-high accounted for 38.8% (n = 93) and 61.2% (n = 147) of the cases, according to the cut-off value of 55.5% for stroma ratio. The Kaplan-Meier analysis showed that patients in the stroma-high group had a worse 5-DFS compared to patients in the stroma-low group (P = 0.031). Multivariable analysis indicated that the T stage, N status, histological grade, ER status, HER-2 gene, and the TSR were potential risk factors of invasive BC patients, which were included into the nomogram (P < 0.10 for all). The nomogram was well calibrated to predict the probability of 5-DFS and the C-index was 0.817, which was higher than any single predictor. A dynamic nomogram was built for convenient use. The area under the curve (AUC) of the nomogram was 0.870, while that of the TNM staging system was 0.723. The Kaplan-Meier analysis showed that the nomogram had a better risk stratification for invasive BC patients than the TNM staging system.

Conclusions: Based on IHC staining of CK on TMAs, this study successfully developed a computerized method for TSR assessment and established a novel nomogram for predicting survival in invasive BC patients.

Prognostic Utility of Prechemoradiotherapy Albumin-to-Alkaline Phosphatase Ratio in Unresectable Locally Advanced Pancreatic Carcinoma Patients

BACKGROUND

We investigated the prognostic usefulness of prechemoradiotherapy (CRT) albumin-to-alkaline phosphatase ratio (AAPR) in unresectable locally advanced pancreatic adenocarcinoma (LAPAC) patients managed with definitive concurrent CRT (CCRT).

METHODS

A sum of 136 LAPAC patients who consecutively underwent definitive CCRT was retrospectively analyzed. The AAPR (serum albumin (g/dL)/serum alkaline phosphatase (IU/L)) was calculated by using the parameters obtained from the routine biochemistry tests on the first day of the CCRT. Ideal AAPR cutoff was sought by utilizing receiver operating characteristic (ROC) curve analysis. The primary and secondary endpoints were the impact of the AAPR on the overall survival (OS) and progression-free survival (PFS) results, respectively.

RESULTS

At a median follow-up of 14.8 months (range: 3.2-85.7), the median PFS and OS times were 7.5 (95% confidence interval (CI): 6.0-9.0) and 14.9 months (95% CI: 11.9-17.9), respectively. The ideal common AAPR cutoff was identified at the rounded 0.46 (area under the curve: 72.3%; sensitivity: 71.2%; specificity: 70.3%) point that dichotomized the patients into two groups: low AAPR (L-AAPR; N = 71) and high AAPR (H-AAPR; N = 65) groups, respectively. Comparative survival analyses showed that the L-AAPR cohort had significantly shorter median PFS (6.8 (95% CI: 5.7-7.9) versus 11.3 (95% CI: 9.9-12.7) months; P = 0.005) and OS (12.8 (95% CI: 10.6-15.0) versus 19.2 (95% CI: 16.9-21.5) months; P = 0.001) durations than their H-AAPR counterparts, separately. Albeit the N1-2 (P = 0.004) and CA 19-9 > 90 U/mL (P = 0.008) were also found to be associated with inferior outcomes, yet the results of the multivariate analyses ascertained the L-AAPR as an independent indicator of diminished PFS (P = 0.003) and OS (P = 0.002) results.

CONCLUSION

The present results proposed that the pretreatment AAPR < 0.46 was a novel independent indicator of adverse PFS and OS in unresectable LAPAC patients undergoing definitive CCRT.