CCR 20th Anniversary Commentary: Simpson's Paradox and Neoadjuvant Trials

Predicting pathological complete response after neoadjuvant chemotherapy: A nomogram combining clinical features and ultrasound semantics in patients with invasive breast cancer

Background

Early identification of response to neoadjuvant chemotherapy (NAC) is instrumental in predicting patients prognosis. However, since a fixed criterion with high accuracy cannot be generalized to molecular subtypes, our study first aimed to redefine grades of clinical response to NAC in invasive breast cancer patients (IBC). And then developed a prognostic model based on clinical features and ultrasound semantics.

Methods

A total of 480 IBC patients were enrolled who underwent anthracycline and taxane-based NAC between 2018 and 2020. The decrease rate of the largest diameter was calculated by ultrasound after NAC and their cut-off points were determined among subtypes. Thereafter, a nomogram was constructed based on clinicopathological and ultrasound-related data, and validated using the calibration curve, receiver operating characteristic (ROC) curve, decision curve analysis (DCA), and clinical impact curve (CIC).

Results

The optimal cut-off points for predicting pCR were 53.23%, 51.56%, 41.89%, and 53.52% in luminal B-like (HER2 negative), luminal B-like (HER2 positive), HER2 positive, and triple-negative, respectively. In addition, time interval, tumor size, molecular subtypes, largest diameter decrease rate, and change of blood perfusion were significantly associated with pCR (all p < 0.05). The prediction model based on the above variables has great predictive power and clinical value.

Conclusion

Taken together, our data demonstrated that calculated cut-off points of tumor reduction rates could be reliable in predicting pathological response to NAC and developed nomogram predicting prognosis would help tailor systematic regimens with high precision.

Trastuzumab-lapatinib as neoadjuvant therapy for HER2-positive early breast cancer: Survival analyses of the CHER-Lob trial

AIM

The Cher-LOB randomised phase II study showed that the combination of lapatinib-trastuzumab plus chemotherapy increases pathologic complete response (pCR) rate compared with chemotherapy plus either trastuzumab or lapatinib. Here, we report the post hoc survival analysis as per treatment arm, pCR and biomarkers.

METHODS

The Cher-LOB study randomised 121 patients with human epidermal growth factor receptor 2-positive, stage II-IIIA breast cancer. A specific protocol to collect recurrence-free survival (RFS) and overall survival (OS) data was designed. Tumour-infiltrating lymphocytes (TILs) and PAM50-intrinsic subtyping were evaluated at baseline.

RESULTS

At 9-year median follow-up, a trend towards RFS improvement with lapatinib-trastuzumab over trastuzumab was observed (hazard ratio [HR] 0.44, 95% confidence interval [CI] 0.18-1.05). Combining treatment arms, pCR was significantly associated with both RFS (HR 0.12, 95% CI 0.03-0.49) and OS (HR 0.12, 95% CI 0.03-0.49). TILs were significantly associated with RFS (HR = 0.978 for each 1% increment). Luminal-A subtype was a significant and independent predictor of improved RFS as compared with other PAM50-based intrinsic subtypes at the multivariate analysis including the most relevant clinicopathologic variables (HR 0.29, 95% CI 0.09-0.94, p = 0.040).

CONCLUSIONS

Cher-LOB trial survival analysis confirmed the prognostic role of pCR and TILs and showed a signal for a better outcome with lapatinib-trastuzumab over trastuzumab.

TRIAL REGISTRATION

NCT00429299.

Neoadjuvant approach as a platform for treatment personalization: focus on HER2-positive and triple-negative breast cancer

The neoadjuvant setting provides unquestionable clinical benefits for high-risk breast cancer (BC) patients, mainly in terms of expansion of locoregional treatment options and prognostic stratification. Additionally, it is also emerging as a strategical tool in the research field. In the present review, by focusing on HER2-positive and triple-negative subtypes, we examined the role of the neoadjuvant setting as a research platform to facilitate and rationalize the placement of escalation strategies, promote the adoption of biomarker-driven approaches for the investigation of de-escalated treatments, and foster the conduction of comprehensive translational analyses, thus ultimately aiming at pursuing treatment personalization. The solid prognostic role of pathologic complete response after neoadjuvant therapy, and its use as a surrogate endpoint to accelerate the drug approval process were discussed. In this context, available data on escalated treatment strategies capable of enhancing pathologic complete response (pCR) rate or improving prognosis of patients with residual disease (RD) after neoadjuvant treatment, were comprehensively reviewed. We also summarized evidence regarding the possibility of obtaining pCR with de-escalated strategies, with particular emphasis on the role of biomarker-driven approaches for patient selection. Pitfalls of the dichotomy of pCR/RD were also deepened, and data on alternative/complementary biomarkers with a possible clinical relevance in this regard were reviewed.

Improving Prognostic Web Calculators: Violation of Preferential Risk Independence

BACKGROUND

Web-based applications are available for prognostication of individual patients. These prognostic models were developed for groups of patients. No one is the average patient, and using these calculators to inform individual patients could provide misleading results.

OBJECTIVE

This article gives an example of paradoxical results that may emerge when indices used for prognosis of the average person are used for care of an individual patient.

METHODS

We calculated the expected mortality risks of stomach cancer and its associated comorbidities. Mortality risks were calculated using data from 140,699 Veterans Administration nursing home residents.

RESULTS

On average, a patient with hypertension has a higher risk of mortality than one without hypertension. Surprisingly, among patients with lung cancer, hypertension is protective and reduces risk of mortality. This paradoxical result is explained by how group-level, average prognosis could mislead individual patients. In particular, average prognosis of lung cancer patients reflects the impact of various comorbidities that co-occur in lung cancer patients. The presence of hypertension, a relatively mild comorbidity of lung cancer, indicates that more serious comorbidities have not occurred. It is not that hypertension is protective; it is the absence of more serious comorbidities that is protective. The article shows how the presence of these anomalies can be checked through the mathematical concept of preferential risk independence.

CONCLUSION

Instead of reporting average risk scores, web-based calculators may improve accuracy of predictions by reporting the unconfounded risks.