Pooled analysis of the prospective trials of gefitinib monotherapy for EGFR-mutant non-small cell lung cancers.

Costa DB ，Kobayashi S ，Tenen DG ，Huberman MS ... -  《LUNG CANCER》

Pooled safety analysis of EGFR-TKI treatment for EGFR mutation-positive non-small cell lung cancer.

Three epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) - afatinib, erlotinib, and gefitinib - are available for the treatment of patients with EGFR mutation-positive non-small cell lung cancer (NSCLC). Given the long-term exposure of such patients to EGFR-TKIs, the toxicological properties of these agents in these individuals may differ from those observed in unselected patients. We compared the frequencies of severe adverse events (AEs) among EGFR mutation-positive NSCLC patients treated with these three EGFR-TKIs. We performed a pooled analysis of severe AEs according to the type of EGFR-TKI administered with the use of data extracted from prospective clinical trials that evaluated the clinical efficacy of gefitinib, erlotinib, or afatinib in NSCLC patients with EGFR mutations. Twenty-one trials published between 2006 and 2014 and including 1468 patients were eligible for analysis. Patients in 13 trials (n=457) received gefitinib, those in 5 trials (n=513) received erlotinib, and those in 3 trials (n=498) received afatinib. Rash and diarrhea of grade ≥3 were significantly more frequent with afatinib therapy than with erlotinib or gefitinib therapy. The frequency of interstitial lung disease (ILD) of grade ≥3 was low (0.6-2.2%) with all three EGFR-TKIs and did not differ significantly among them. Gefitinib was associated with a significantly higher frequency of hepatotoxicity of grade ≥3 compared with erlotinib or afatinib. The overall frequency of AEs leading to treatment withdrawal was 6.1% (83 of 1354 evaluable patients), with such AEs occurring significantly more often with afatinib or gefitinib than with erlotinib. The most common withdrawal AEs were skin toxicity, ILD, and hepatotoxicity. Such information on AEs should facilitate selection of the most appropriate EGFR-TKI for EGFR mutation-positive NSCLC patients with regard to mitigation of the risk for certain types of toxicity.

Takeda M ，Okamoto I ，Nakagawa K 《-》

Clinical outcomes of gefitinib and erlotinib in patients with NSCLC harboring uncommon EGFR mutations: A pooled analysis of 438 patients.

The purpose of this study was to investigate the outcomes of gefitinib and erlotinib in patients with non-small cell lung cancer (NSCLC) with uncommon epidermal growth factor receptor (EGFR) mutations. Relevant researches were identified by a literature search of the PubMed database. Patients with EGFR mutations other than exon 19 deletion and L858R were eligible for the study. Clinical outcomes included objective response rate (ORR), progression free survival (PFS), and overall survival (OS). We categorized all uncommon EGFR mutations as: single uncommon EGFR mutations and compound mutations that containing 2 or more kinds of EGFR mutations. We also assessed outcomes in patients categorized by EGFR-TKIs: (1) gefitinib group; (2) erlotinib group. A total of 438 patients with NSCLC harboring uncommon EGFR mutations were included in this study. The ORR for gefitinib and erlotinib was 43.8 %, with a median PFS (mPFS) of 6.00 months and a median OS (mOS) of 20.50 months. Patients with compound mutations had an ORR of 56.3 % and an mPFS of 8.10 months. Both of them were significantly better than these in patients with single uncommon EGFR mutation, which were 29.3 % and 3.90 months, respectively (odds ratio (ORa): 2.74, 95 % confidence interval (CI): 1.86-4.05, P < 0.001; hazard ratio (HR): 0.58, 95 % CI: 0.48-0.71, P < 0.001). Moreover, patients with compound mutations containing 19 deletion or L858R had a superior response and survival benefits compared to patients with other compound mutation patterns. In addition, the gefitinib group showed a favorable efficacy advantage (P = 0.003) and PFS benefit (P = 0.021) compared to the erlotinib group. Uncommon EGFR mutations exhibit favorable but inconsistent treatment responses and survival outcomes to gefitinib and erlotinib, which are closely related to the mutation pattern, the cooccurring partner mutant genes, and the type of EGFR-TKIs received.

Wang C ，Zhao K ，Hu S ，Dong W ，Gong Y ，Li M ，Xie C ... -  《-》

Pooled analysis of the reports of erlotinib after failure of gefitinib for non-small cell lung cancer.

The use of erlotinib after gefitinib failure in patients with non-small cell lung cancer (NSCLC) is not clearly clarified in clinical practice. We sought to compile the available clinical reports to better understand the effectiveness of erlotinib after failure of gefitinib. We searched published reports including erlotinib and gefitinib. Eleven reports were identified (published between November 2004 and December 2008). Advanced NSCLC who documented progressive disease (PD) for gefitinib 250 mg/day, received erlotinib 150 mg once daily. A total of 106 patients were pooled from these studies. Asian was observed in 70.8%, women in 72.6%, adenocarcinoma in 85.1%, never smoker in 75.3%. In erlotinib therapy, there was observed in 9.9% in partial response (PR), 18.9% in stable disease (SD) and 70.8% in PD. Disease control (DC) rate for gefitinib and erlotinib was 71.7% and 29.2%, respectively. No significant difference of disease control rate (37.5% vs 21.7%, p=0.1503) and response rate (6.3% vs 8.7%, p=1.000) was observed between patients with EGFR mutations and those with wild type EGFR. The significantly different response on erlotinib therapy was observed in patients who had shown SD for gefitinib therapy (p=0.0095) and those who had a PFS of more than 6 months during gefitinib treatment (p=0.0261). The common toxicities were skin rash and diarrhea. Erlotinib may produce clinical benefits in patients who had shown long SD on prior gefitinib therapy. Moreover, EGFR mutations were not positive predictors for erlotinib response after gefitinib failure.

Kaira K ，Naito T ，Takahashi T ，Ayabe E ，Shimoyama R ，Kaira R ，Ono A ，Igawa S ，Shukuya T ，Murakami H ，Tsuya A ，Nakamura Y ，Endo M ，Yamamoto N ... -  《-》

Comparison of Two Modern Survival Prediction Tools, SORG-MLA and METSSS, in Patients With Symptomatic Long-bone Metastases Who Underwent Local Treatment With Surgery Followed by Radiotherapy and With Radiotherapy Alone.

Survival estimation for patients with symptomatic skeletal metastases ideally should be made before a type of local treatment has already been determined. Currently available survival prediction tools, however, were generated using data from patients treated either operatively or with local radiation alone, raising concerns about whether they would generalize well to all patients presenting for assessment. The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA), trained with institution-based data of surgically treated patients, and the Metastases location, Elderly, Tumor primary, Sex, Sickness/comorbidity, and Site of radiotherapy model (METSSS), trained with registry-based data of patients treated with radiotherapy alone, are two of the most recently developed survival prediction models, but they have not been tested on patients whose local treatment strategy is not yet decided. (1) Which of these two survival prediction models performed better in a mixed cohort made up both of patients who received local treatment with surgery followed by radiotherapy and who had radiation alone for symptomatic bone metastases? (2) Which model performed better among patients whose local treatment consisted of only palliative radiotherapy? (3) Are laboratory values used by SORG-MLA, which are not included in METSSS, independently associated with survival after controlling for predictions made by METSSS? Between 2010 and 2018, we provided local treatment for 2113 adult patients with skeletal metastases in the extremities at an urban tertiary referral academic medical center using one of two strategies: (1) surgery followed by postoperative radiotherapy or (2) palliative radiotherapy alone. Every patient's survivorship status was ascertained either by their medical records or the national death registry from the Taiwanese National Health Insurance Administration. After applying a priori designated exclusion criteria, 91% (1920) were analyzed here. Among them, 48% (920) of the patients were female, and the median (IQR) age was 62 years (53 to 70 years). Lung was the most common primary tumor site (41% [782]), and 59% (1128) of patients had other skeletal metastases in addition to the treated lesion(s). In general, the indications for surgery were the presence of a complete pathologic fracture or an impending pathologic fracture, defined as having a Mirels score of ≥ 9, in patients with an American Society of Anesthesiologists (ASA) classification of less than or equal to IV and who were considered fit for surgery. The indications for radiotherapy were relief of pain, local tumor control, prevention of skeletal-related events, and any combination of the above. In all, 84% (1610) of the patients received palliative radiotherapy alone as local treatment for the target lesion(s), and 16% (310) underwent surgery followed by postoperative radiotherapy. Neither METSSS nor SORG-MLA was used at the point of care to aid clinical decision-making during the treatment period. Survival was retrospectively estimated by these two models to test their potential for providing survival probabilities. We first compared SORG to METSSS in the entire population. Then, we repeated the comparison in patients who received local treatment with palliative radiation alone. We assessed model performance by area under the receiver operating characteristic curve (AUROC), calibration analysis, Brier score, and decision curve analysis (DCA). The AUROC measures discrimination, which is the ability to distinguish patients with the event of interest (such as death at a particular time point) from those without. AUROC typically ranges from 0.5 to 1.0, with 0.5 indicating random guessing and 1.0 a perfect prediction, and in general, an AUROC of ≥ 0.7 indicates adequate discrimination for clinical use. Calibration refers to the agreement between the predicted outcomes (in this case, survival probabilities) and the actual outcomes, with a perfect calibration curve having an intercept of 0 and a slope of 1. A positive intercept indicates that the actual survival is generally underestimated by the prediction model, and a negative intercept suggests the opposite (overestimation). When comparing models, an intercept closer to 0 typically indicates better calibration. Calibration can also be summarized as log(O:E), the logarithm scale of the ratio of observed (O) to expected (E) survivors. A log(O:E) > 0 signals an underestimation (the observed survival is greater than the predicted survival); and a log(O:E) < 0 indicates the opposite (the observed survival is lower than the predicted survival). A model with a log(O:E) closer to 0 is generally considered better calibrated. The Brier score is the mean squared difference between the model predictions and the observed outcomes, and it ranges from 0 (best prediction) to 1 (worst prediction). The Brier score captures both discrimination and calibration, and it is considered a measure of overall model performance. In Brier score analysis, the "null model" assigns a predicted probability equal to the prevalence of the outcome and represents a model that adds no new information. A prediction model should achieve a Brier score at least lower than the null-model Brier score to be considered as useful. The DCA was developed as a method to determine whether using a model to inform treatment decisions would do more good than harm. It plots the net benefit of making decisions based on the model's predictions across all possible risk thresholds (or cost-to-benefit ratios) in relation to the two default strategies of treating all or no patients. The care provider can decide on an acceptable risk threshold for the proposed treatment in an individual and assess the corresponding net benefit to determine whether consulting with the model is superior to adopting the default strategies. Finally, we examined whether laboratory data, which were not included in the METSSS model, would have been independently associated with survival after controlling for the METSSS model's predictions by using the multivariable logistic and Cox proportional hazards regression analyses. Between the two models, only SORG-MLA achieved adequate discrimination (an AUROC of > 0.7) in the entire cohort (of patients treated operatively or with radiation alone) and in the subgroup of patients treated with palliative radiotherapy alone. SORG-MLA outperformed METSSS by a wide margin on discrimination, calibration, and Brier score analyses in not only the entire cohort but also the subgroup of patients whose local treatment consisted of radiotherapy alone. In both the entire cohort and the subgroup, DCA demonstrated that SORG-MLA provided more net benefit compared with the two default strategies (of treating all or no patients) and compared with METSSS when risk thresholds ranged from 0.2 to 0.9 at both 90 days and 1 year, indicating that using SORG-MLA as a decision-making aid was beneficial when a patient's individualized risk threshold for opting for treatment was 0.2 to 0.9. Higher albumin, lower alkaline phosphatase, lower calcium, higher hemoglobin, lower international normalized ratio, higher lymphocytes, lower neutrophils, lower neutrophil-to-lymphocyte ratio, lower platelet-to-lymphocyte ratio, higher sodium, and lower white blood cells were independently associated with better 1-year and overall survival after adjusting for the predictions made by METSSS. Based on these discoveries, clinicians might choose to consult SORG-MLA instead of METSSS for survival estimation in patients with long-bone metastases presenting for evaluation of local treatment. Basing a treatment decision on the predictions of SORG-MLA could be beneficial when a patient's individualized risk threshold for opting to undergo a particular treatment strategy ranged from 0.2 to 0.9. Future studies might investigate relevant laboratory items when constructing or refining a survival estimation model because these data demonstrated prognostic value independent of the predictions of the METSSS model, and future studies might also seek to keep these models up to date using data from diverse, contemporary patients undergoing both modern operative and nonoperative treatments. Level III, diagnostic study.

Lee CC ，Chen CW ，Yen HK ，Lin YP ，Lai CY ，Wang JL ，Groot OQ ，Janssen SJ ，Schwab JH ，Hsu FM ，Lin WH ... -  《-》