Dose escalation in advanced floor of the mouth cancer: a pilot study using a combination of IMRT and stereotactic boost

High PD-L1 expression on immune cells along with increased density of tumor-infiltrating lymphocytes predicts a favorable survival outcome for patients with loco-regionally advanced head and neck cancer: early results from a prospective study

Introduction

In the era of personalized medicine and treatment optimization, use of immune biomarkers holds promise for estimating the prognosis of patients with head and neck squamous cell carcinoma (HNSCC) undergoing definitive treatment.

Methods

To evaluate the prognostic potential of immune biomarkers, we conducted a prospective monocentric cohort study with loco-regionally advanced HNSCC patients indicated for definitive radiotherapy/radiochemotherapy at the Department of Oncology, Ostrava University Hospital, Czech Republic, between June 2020 and August 2023. We focused on the expression of programmed death ligand 1 (PD-L1) and tumor-infiltrating lymphocytes (TILs) relative to overall survival (OS) and specific survival rates. Associations between biomarkers and survival rates were assessed by crude and adjusted hazard ratios (cHR, aHR, respectively) obtained from Cox proportional hazards regression.

Results

Among a total of 55 patients within a median follow-up of 19.7 months, there were 21 (38.2%) all-cause deaths and 15 (27.3%) cancer-related deaths. An overall survival (OS) rate of 61.8% and a disease-specific survival (DSS) rate of 72.7% were recorded. A significant association between survival rates and a ≥10% difference in PD-L1 expression on immune versus tumor cells (high PD-L1IC expression) was documented regardless of the type of analysis (univariate or multivariate). In addition, a stronger association was confirmed for OS and the composite biomarker high PD-L1IC expression along with either median-higher CD8+ TIL count or increased TIL density ≥30%, as indicated by an aHR of 0.08 (95% CI, 0.01 to 0.52) and 0.07 (95% CI, 0.01 to 0.46), respectively. Similar results were demonstrated for other specific survival rates.

Discussion

The early outcomes of the present study suggest the utility of a strong prognostic factor involving a composite biomarker high PD-L1IC expression along with increased TIL density in HNSCC patients undergoing definitive radiotherapy and radiochemotherapy.

Trial registration

The study is registered with Clinicaltrials.gov. - NCT05941676.

Current Treatment Strategies and Risk Stratification for Oral Carcinoma

Management of oral cavity squamous cell carcinoma (OSCC) involves a multidisciplinary team approach. Surgery is ideally the primary treatment option for nonmetastatic OSCC, and less invasive curative surgical approaches are preferred in early-stage disease to minimize surgical-related morbidity. For patients at high risk of recurrence, adjuvant treatment using radiation therapy or chemoradiation is often used. Systemic therapy may also be used in the neoadjuvant setting (for advanced-stage disease with the intent of mandibular preservation) or in the palliative setting (for nonsalvageable locoregional recurrence and/or distant metastases). Patient involvement in treatment decision is the key for patient-driven management, particularly in clinical situation with poor prognosis, for example, early postoperative recurrence before planned adjuvant therapy.

A nomogram for predicting overall survival of patients with squamous cell carcinoma of the floor of the mouth: a population-based study

BACKGROUND

Floor of mouth squamous cell carcinoma (SCCFOM) is a rare but aggressive malignancy with 5-year overall survival (OS) rates below 40% in published studies. However, the clinicopathological predictors of the prognosis of SCCFOM remain undefined. We aimed to establish a model to predict the survival outcomes of SCCFOM.

METHODS

We searched the Surveillance, Epidemiology, and End Results (SEER) database for patients diagnosed with SCCFOM between 2000 and 2017. Data on patient demographics, treatment modalities, and survival outcomes were retrieved. Risk factors for OS were evaluated by survival and Cox regression analyses. A nomogram for OS was developed based on the multivariate model and split the patients into high- and low-risk cohorts based on cutoff values.

RESULTS

Overall, 2014 SCCFOM patients were included in this population-based study. Multivariate Cox regression showed that age, married status, grade, American Joint Committee on Cancer stage, radiotherapy, chemotherapy, and surgery were significant risk factors for survival. A nomogram was established using the regression model. The C-indices, areas under the receiver operating characteristic curves, and calibration plots demonstrated the reliable performance of the nomogram. Patients assigned to the high-risk group had a significantly lower survival rate.

CONCLUSIONS

The nomogram predicting survival outcomes of SCCFOM patients based on clinical information showed good discriminative ability and prognostic accuracy. Our nomogram could be used to predict the survival probabilities for SCCFOM patients at different timepoints.

Virtual clinical trial based on outcome modeling with iteratively redistributed extrapolation data

Virtual clinical trials (VCTs) can potentially simulate clinical trials on a computer, but their application with a limited number of past clinical cases is challenging due to the biased estimation of the statistical population. In this study, we developed ExMixup, a novel training technique based on machine learning, using iteratively redistributed extrapolated data. Information obtained from 100 patients with prostate cancer and 385 patients with oropharyngeal cancer was used to predict the recurrence after radiotherapy. Model performance was evaluated by developing outcome prediction models based on three types of training methods: training with original data (baseline), interpolation data (Mixup), and interpolation + extrapolation data (ExMixup). Two types of VCTs were conducted to predict the treatment response of patients with distinct characteristics compared to the training data obtained from patient cohorts categorized under risk classification or cancer stage. The prediction models developed with ExMixup yielded concordance indices (95% confidence intervals) of 0.751 (0.719-0.818) and 0.752 (0.734-0.785) for VCTs on the prostate and oropharyngeal cancer datasets, respectively, which significantly outperformed the baseline and Mixup models (P < 0.01). The proposed approach could enhance the ability of VCTs to predict treatment results in patients excluded from past clinical trials.

High-dose stereotactic radiotherapy boost in the treatment of squamous cell carcinoma of the head and neck region

Background

Surgical resection with adjuvant concurrent radiochemotherapy is the standard of care for stage III–IV oral cavity cancer. In some cases, the dynamic course of the disease is out of the prepared schedule of treatment. In that event, a stereotactic radiosurgery boost might be the only chance for disease control.

Case presentation

Here, we present a case study of a patient with oral cancer who underwent surgery. During adjuvant radiotherapy, a metastatic cervical lymph node was diagnosed based on fine-needle aspiration biopsy. To increase the total dose to the metastatic tumor, a stereotactic radiosurgery boost of 1 × 18 Gy was performed two days after the last fraction of conventional radiotherapy. The early and late tolerance of this treatment were positive. During the 18-month follow-up, locoregional recurrence was not detected. The patient died due to secondary malignancy.

Conclusions

This paper shows that a stereotactic radiosurgery boost added to adjuvant conventional radiotherapy is an effective approach permitting the maintenance of good local control in well-selected patients.