Developing an objective marker to optimize patient selection and predict survival benefit in early-phase cancer trials

Validation and comparison of prognostic scoring systems in patients with head and neck squamous cell carcinoma treated with nivolumab

OBJECTIVE

Several scoring systems have been developed to predict prognosis in patients with refractory cancer. We aimed to validate eight scoring systems and determine the best method for predicting the prognosis of head and neck squamous cell carcinoma treated with nivolumab.

METHODS

This multicentre retrospective study involved 154 patients with recurrent and/or metastatic head and neck squamous cell carcinoma treated with nivolumab between 2017 and 2020. Oncological outcomes were assessed according to the scoring systems, including MD Anderson Cancer Center + neutrophil-to-lymphocyte ratio and Hammersmith scores. Objective response, overall survival and progression-free survival were evaluated using logistic regression and Cox proportional hazards analyses. Receiver operating curve analysis was used to calculate the area under the curve and estimate the efficacy of each score.

RESULTS

No significant associations were found between the responses and any score. Seven of the eight scoring systems were associated with disease control (odds ratio, 0.26-0.70). Amongst the eight scoring systems, MD Anderson Cancer Center + neutrophil-to-lymphocyte ratio showed the highest area under the curve for predicting response and disease control. Seven scoring systems were prognostic factors for progression-free survival (hazard ratio, 1.22-1.95). All eight scoring systems were prognostic factors for overall survival (hazard ratio, 1.62-3.83). According to the time-dependent receiver operating characteristics analysis for overall survival, the Hammersmith scoring system had the best predictive ability at 3 months, and the MD Anderson Cancer Center + neutrophil-to-lymphocyte ratio scoring system had the highest area under the curve between 6 and 24 months.

CONCLUSIONS

MD Anderson Cancer Center + neutrophil-to-lymphocyte ratio and Hammersmith scoring systems were better predictors of prognosis in patients with head and neck squamous cell carcinoma treated with nivolumab.

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.

Improving patient selection for immuno-oncology phase 1 trials: External validation of six prognostic scores in a French Cancer Center

We compared the performance of six prognostic scores (Royal Marsden Hospital, MDACC: MD Anderson Clinical Center and MDACC + NLR: neutrophil-to-lymphocyte ratio, MD Anderson - immune checkpoint inhibitors (MDA-ICI), GRIm: Gustave Roussy Immune Score and LIPI: Lung Immune Prognostic Index) in predicting overall survival (OS) in phase I trial patients treated with immune checkpoint inhibitors (ICI). Medical records of patients with advanced solid tumors enrolled in ICI phase I trials between 2015 and 2018 at Institut Universitaire du Cancer de Toulouse-Oncopole were reviewed. The performance of prognostic scores on OS was compared using different criteria. A total of 259 patients were included. Median age was 63 years (range: 18-83). Main primary cancers were melanoma (19%), head and neck (16%), lung (13%) and bladder (10%). With a median follow-up of 15 months (95% confidence interval [CI] = [11.6;17.5]), median OS was 12.5 months (95% CI = [10.3;16.0]). All scores were associated with OS. The MDACC, LIPI and GRIm scores performed better than the others. Concordance of risk group assignment between the scoring systems was poor. According to our results, the MDACC, GRIm and LIPI scores better suited to ICI phase I settings. Adequate scoring would allow better patient selection in early ICI trials, especially during the critical period of dose escalation, and in proof-of-concept expansion cohorts.

Clinical Predictors of Early Trial Discontinuation for Patients Participating in Phase I Clinical Trials in Oncology

Simple Summary

About 20% of patients with cancer who participate in a phase I clinical trial discontinue the trial early. Early trial discontinuation is undesirable both for the wellbeing of the patient as well as for the trial efficiency and the development of new anticancer drugs. We investigated which clinical predictors at baseline were significantly associated with early trial discontinuation of patients with cancer who participated in phase I clinical trials. The clinical predictors which were identified in this study were hyponatremia, elevated alkaline phosphatase level, performance score of 1 or higher and opioid use. Hyponatremia especially, which was the strongest predictor, should be considered to be used as an additional eligibility criterion in order to reduce the early trial discontinuation of patients with cancer who participate in phase I clinical trials.

Abstract

Despite stringent eligibility criteria for trial participation, early discontinuation often occurs in phase I trials. To better identify patients unlikely to benefit from phase I trials, we investigated predictors for early trial discontinuation. Data from 415 patients with solid tumors who participated in 66 trials were pooled for the current analysis. Early trial discontinuation was defined as (i) trial discontinuation within 28 days after start of treatment or (ii) discontinuation before administration of the first dosage in eligible patients. Multilevel logistic regression analyses were conducted to identify predictors for early trial discontinuation. Eighty-two participants (20%) demonstrated early trial discontinuation. Baseline sodium level below the lower limit of normal (OR = 2.95, 95%CI = 1.27–6.84), elevated alkaline phosphatase level > 2.5 times the upper limit of normal (OR = 2.72, 95%CI = 1.49–4.99), performance score ≥ 1 (OR = 2.07, 95%CI = 1.03–4.19) and opioid use (OR = 1.82, 95%CI = 1.07–3.08) were independent predictors for early trial discontinuation. Almost 50% of the patients with hyponatremia and all four patients in whom all four predictors were present together discontinued the trial early. Hyponatremia, elevated alkaline phosphatase level, performance score ≥ 1 and opioid use were identified as significant predictors for early trial discontinuation. Hyponatremia was the strongest predictor and deserves consideration for inclusion in eligibility criteria for future trials.

A Predictive Score of Antitumour Activity of Novel Agents in Cancer Patients Treated in Early Phase Studies

INTRODUCTION

Phase I trials aim to determine the maximum-tolerated dose of a particular drug while minimizing the number of patients exposed to either sub-therapeutic doses or severe toxicity. Thus, patient selection for phase I trials is a key component of any clinical trial design. Though several studies have been made to address this issue, patient selection still represents a major clinical challenge that needs further investigation.

METHODS

Twenty-nine baseline clinical and analytical characteristics of 773 consecutive patients treated in phase I trials between 2008 and 2016 in START Madrid-CIOCC were analysed and correlated to objective response (OR), progression-free survival, median overall survival, toxicity, and treatment type. The ones associated to OR in the univariate analysis were included in the stepwise logistic regression multivariate and Cox analysis. The statistically significant ones were included in a predictive score (named here as the Madrid score) of antitumour activity.

RESULTS

Body mass index (BMI) >25 (p = 0.027), two or less previous lines of treatment (p = 0.007), and normal levels of alkaline phosphatase (ALP) (p = 0.007) were found to positively correlate to radiological response. A Madrid score was generated using these three factors as predictive parameters: compared to a score of 2-3 (where 2 or 3 of these variables are altered), a score of 0-1 is associated with longer survival time (11.6 vs. 8.6 months; p = 0.005) and overall response (17 vs. 7.6%; p = 0.003).

CONCLUSION

The predictive Madrid score, based on the BMI, number of prior lines of treatment, and ALP levels, might be helpful to accurately select patients who would benefit from oncology phase I clinical trials.

Survival in Early Phase Immuno-Oncology Trials: Development and Validation of a Prognostic Index

Background

Immuno-oncology (IO) is rapidly evolving in early drug development. We aimed to develop and prospectively validate a prognostic index for patients treated in IO phase I trials to assist with patient selection.

Methods

The development cohort included 192 advanced solid tumor patients treated in 13 IO phase I trials, targeting immune checkpoint and/or co-stimulatory molecules. A prognostic scoring system was developed from multivariate survival analysis of 10 clinical factors, and subsequently validated in two independent validation cohorts (n = 152 and n = 80).

Results

In the development cohort, median age was 57.5 years (range = 20.4-84.8 years). Median progression-free survival and overall survival (OS) were 13.4 and 73.6 weeks, respectively, 90-day mortality was 16%, and overall response rate was 20%. In multivariate analysis, Eastern Cooperative Oncology Group performance status greater than or equal to 1 (hazard ratio [HR] = 3.2, 95% confidence interval [CI] = 1.8 to 5.7; P < .001), number of metastatic sites greater than 2 (HR = 2.0, 95% CI = 1.3 to 3.1; P = .003), and albumin less than the lower limit of normal (HR = 1.8, 95% CI = 1.2 to 2.7; P = .007) were independent prognostic factors; comprising the Princess Margaret Immuno-oncology Prognostic Index (PM-IPI). Patients with a score of 2-3 compared with patients with a score of 0-1 had shorter OS (HR = 3.4, 95% CI = 1.9 to 6.1; P < .001), progression-free survival (HR = 2.3, 95% CI = 1.7 to 3.2; P < .001), higher 90-day mortality (odds ratio = 8.1, 95% CI = 3.0 to 35.4; P < .001), and lower overall response rate (odds ratio = 0.4, 95% CI = 0.2 to 0.8; P = .019). The PM-IPI retained prognostic ability in both validation cohorts and performed better than previously published phase I prognostic scores for predicting OS in all three cohorts.

Conclusions

The PM-IPI is a validated prognostic score for patients treated in phase I IO trials and may aid in improving patient selection.

Survival outcome and prognostic model of patients with colorectal cancer on phase 1 trials

Background Patients with metastatic colorectal cancer (mCRC) who progress on standard therapies may be eligible for phase I trials. To better delineate the risk-benefit ratio, we assessed toxicities, clinical outcomes and prognostic factors. Methods Records of mCRC patients on phase I trials at our institution over 18 years were reviewed. Univariable (UVA) and multivariable analyses (MVA) were undertaken and a prognostic model developed. Results There were 187 enrollments on 37 phase I trials. Median age was: 59 (29-83) years and number of prior therapies: 3 (0-8). The clinical benefit rate (CBR): response (5.6%) + stable disease, was 43.1%. Median progression free survival (PFS) and overall survival (OS) was 7.7 weeks and 43.7 weeks, respectively. The MVA identified age > 60 years (HR 1.63, p < 0.004), albumin<3.5 g/dL (HR 3.69, p < 0.001), direct bilirubin>ULN (HR1.69, p < 0.01), and WBC ≥ 5.2 k/uL (HR 1.97, p < 0.001) as negative prognostic factors. A risk score based on the MVA revealed that patients with a score of 0-1 had an improved OS (58.7 weeks) compared to a score of 2 (49.9 weeks, p < 0.01) and 3 (14.1 weeks, p < 0.001). Conclusions Phase 1 trials may offer similar or better clinical outcome for mCRC patients than standard third line therapies; the prognostic model could assist in selecting appropriate patients.

PRognostic factor of Early Death In phase II Trials or the end of 'sufficient life expectancy' as an inclusion criterion? (PREDIT model)

Background

Optimizing patient selection is a necessary step to design better clinical trials. ‘Life expectancy’ is a frequent inclusion criterion in phase II trial protocols, a measure that is subjective and often difficult to estimate. The aim of this study was to identify factors associated with early death in patients included in phase II studies.

Methods

We retrospectively collected medical records of patients with advanced solid tumors included in phase II trials in two French Comprehensive Cancer Centers (Bordeaux, Center 1 set; Lille, Center 2 set). We analyzed patients’ baseline characteristics. Predictive factors associated with early death (mortality at 3 months) were identified by logistic regression. We built a model (PREDIT, PRognostic factor of Early Death In phase II Trials) based on prognostic factors isolated from the final multivariate model.

Results

Center 1 and 2 sets included 303 and 227 patients, respectively. Patients from Center 1 and 2 sets differed in tumor site, urological (26 % vs 15 %) and gastrointestinal (18 % vs 28 %) and in lung metastasis incidence (10 % vs 49 %). Overall survival (OS) at 3 months was 88 % (95 % CI [83.5; 91.0], Center 1 set) and 91 % (95 % CI [86.7; 94.2], Center 2 set). Presence of a ‘life expectancy’ inclusion criterion did not improve the 3-month OS (HR 0.6, 95 % CI [0.2; 1.2], p = 0.2325). Independent factors of early death were an ECOG score of 2 (OR 13.3, 95%CI [4.1; 43.4]), hyperleukocytosis (OR 5.5, 95 % CI [1.9; 16.3]) and anemia (OR 2.8, 95 % CI [1.1; 7.1]). Same predictive factors but with different association levels were found in the Center 2 set. Using the Center 1 set, ROC analysis shows a good discrimination to predict early death (AUC: 0.89 at 3 months and 0.86 at 6 months).

Conclusions

Risk modeling in two independent cancer populations based on simple clinical parameters showed that baseline ECOG of 2, hyperleukocytosis and anemia are strong early-death predictive factors. This model allows identifying patients who may not benefit from a phase II trial investigational drug and may, therefore, represent a helpful tool to select patients for phase II trial entry.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-016-2819-7) contains supplementary material, which is available to authorized users.

Challenges Facing Early Phase Trials Sponsored by the National Cancer Institute: An Analysis of Corrective Action Plans to Improve Accrual

Accruing patients in a timely manner represents a significant challenge to early phase cancer clinical trials. The NCI Cancer Therapy Evaluation Program analyzed 19 months of corrective action plans (CAP) received for slow-accruing phase I and II trials to identify slow accrual reasons, evaluate whether proposed corrective actions matched these reasons, and assess the CAP impact on trial accrual, duration, and likelihood of meeting primary scientific objectives. Of the 135 CAPs analyzed, 69 were for phase I trials and 66 for phase II trials. Primary reasons cited for slow accrual were safety/toxicity (phase I: 48%), design/protocol concerns (phase I: 42%, phase II: 33%), and eligibility criteria (phase I: 41%, phase II: 35%). The most commonly proposed corrective actions were adding institutions (phase I: 43%, phase II: 85%) and amending the trial to change eligibility or design (phase I: 55%, phase II: 44%). Only 40% of CAPs provided proposed corrective actions that matched the reasons given for slow accrual. Seventy percent of trials were closed to accrual at time of analysis (phase I = 48; phase II = 46). Of these, 67% of phase I and 70% of phase II trials met their primary objectives, but they were active three times longer than projected. Among closed trials, 24% had an accrual rate increase associated with a greater likelihood of meeting their primary scientific objectives. Ultimately, trials receiving CAPs saw improved accrual rates. Future trials may benefit from implementing CAPs early in trial life cycles, but it may be more beneficial to invest in earlier accrual planning. Clin Cancer Res; 22(22); 5408-16. ©2016 AACRSee related commentary by Mileham and Kim, p. 5397.

Chemical reaction-induced multi-molecular polarization (CRIMP)

Here we present a novel hyperpolarization method, Chemical Reaction-Induced Multi-molecular Polarization (CRIMP), which could be applied to the study of several in vivo processes simultaneously including glycolysis, TCA cycle, fatty acid synthesis and pH mapping. Through the use of non-enzymatic decarboxylation, we generate four hyperpolarized imaging agents from hyperpolarized 1,2-(13)C pyruvic acid.

The neutrophil-lymphocyte ratio and its utilisation for the management of cancer patients in early clinical trials

Background:

Inflammation is critical to the pathogenesis and progression of cancer, with a high neutrophil–lymphocyte ratio (NLR) associated with poor prognosis. The utility of studying NLR in early clinical trials is unknown.

Methods:

This retrospective study evaluated 1300 patients treated in phase 1 clinical trials between July 2004 and February 2014 at the Royal Marsden Hospital (RMH), UK. Data were collected on patient characteristics and baseline laboratory parameters.

Results:

The test cohort recruited 300 patients; 53% were female, 35% ECOG 0 and 64% ECOG 1. RMH score was 0–1 in 66% and 2–3 in 34%. The median NLR was 3.08 (IQR 2.06–4.49). Median OS for the NLR quartiles was 10.5 months for quartile-1, 10.3 months for quartile-2, 7.9 months for quartile-3 and 6.5 months for quartile-4 (P<0.0001). Univariate analysis identified RMH score (HR=0.55, P<0.0001), ECOG (HR=0.62, P=0.002) and neutrophils (HR=0.65, P=0.003) to be associated with OS. In multivariate analysis, adjusting for RMH score, ECOG, neutrophils and tumour type, NLR remained significantly associated with OS (P=0.002), with no association with therapeutic steroid use. These results were validated in a further 1000 cancer patients. In the validation cohort, NLR was able to discriminate for OS (P=0.004), as was the RMH score. This was further improved on in the RMH score+NLR50 and RMH score+Log₁₀NLR models, with an optimal NLR cutoff of 3.0.

Conclusions:

NLR is a validated independent prognostic factor for OS in patients treated in phase 1 trials. Combining the NLR with the RMH score improves the discriminating ability for OS.

An inflammation based score can optimize the selection of patients with advanced cancer considered for early phase clinical trials

BACKGROUND

Adequate organ function and good performance status (PS) are common eligibility criteria for phase I trials. As inflammation is pathogenic and prognostic in cancer we investigated the prognostic performance of inflammation-based indices including the neutrophil (NLR) and platelet to lymphocyte ratio (PLR).

METHODS

We studied inflammatory scores in 118 unselected referrals. NLR normalization was recalculated at disease reassessment. Each variable was assessed for progression-free (PFS) and overall survival (OS) on uni- and multivariate analyses and tested for 90 days survival (90DS) prediction using receiving operator curves (ROC).

RESULTS

We included 118 patients with median OS 4.4 months, 23% PS>1. LDH≥450 and NLR≥5 were multivariate predictors of OS (p<0.001). NLR normalization predicted for longer OS (p<0.001) and PFS (p<0.05). PS and NLR ranked as most accurate predictors of both 90DS with area under ROC values of 0.66 and 0.64, and OS with c-score of 0.69 and 0.60. The combination of NLR+PS increased prognostic accuracy to 0.72. The NLR was externally validated in a cohort of 126 subjects.

CONCLUSIONS

We identified the NLR as a validated and objective index to improve patient selection for experimental therapies, with its normalization following treatment predicting for a survival benefit of 7 months. Prospective validation of the NLR is warranted.