Patterns of lymph node involvement for oral cavity squamous cell carcinoma.

AIM: Whereas the prevalence of lymph node level (LNL) involvement in oral cavity squamous cell carcinomas (OCSCC) has been reported, the details of lymphatic progression patterns are insufficiently quantified. We investigate how the risk of metastases in each LNL depends on the involvement of adjacent LNLs, T-category, subsite, primary tumor lateralization, and other risk factors. METHODS: We retrospectively analyzed patients with newly diagnosed OCSCC from two institutions, totaling 348 patients. Involvement of LNLs I-V was recorded individually based on pathology after neck dissection with clinicopathological factors. The dataset is publicly available in a previously developed web-app, which allows querying patients with specific combinations of co-involved LNLs and tumor characteristics. RESULTS: Ipsilateral involvement prevalence of levels I-III was higher for advanced T-category (T3/T4) patients (32 %, 38 %, 14 %) compared to early (T1/T2) patients (14 %, 23 %, 11 %). Involvement of level I increased the involvement probability in levels II and III. Similarly, involvement of level II increased the involvement probability in levels I and III. However, there was significant isolated involvement of level I or II. Advanced nodal involvement (>1 LNL involved) was more frequent for patients with extracapsular extension. Overall contralateral involvement in levels I-III was 7 %, 4 %, 3 % and more frequent for more advanced ipsilateral involvement and for midline-crossing tumors. Involvement of levels IV and V was rare: 3 % ipsilateral and 1 % contralateral in both levels. CONCLUSIONS: Detailed quantification of LNL involvement in OCSCC depending on involvement of adjacent LNLs and clinicopathological factors may allow further personalizing guidelines on elective nodal treatment.

Modelling the lymphatic metastatic progression pathways of OPSCC from multi-institutional datasets.

The elective clinical target volume (CTV-N) in oropharyngeal squamous cell carcinoma (OPSCC) is currently based mostly on the prevalence of lymph node metastases in different lymph node levels (LNLs) for a given primary tumor location. We present a probabilistic model for ipsilateral lymphatic spread that can quantify the microscopic nodal involvement risk based on an individual patient's T-category and clinical involvement of LNLs at diagnosis. We extend a previously published hidden Markov model (HMM), which models the LNLs (I, II, III, IV, V, and VII) as hidden binary random variables (RVs). Each represents a patient's true state of lymphatic involvement. Clinical involvement at diagnosis represents the observed binary RVs linked to the true state via sensitivity and specificity. The primary tumor and the hidden RVs are connected in a graph. Each edge represents the conditional probability of metastatic spread per abstract time-step, given disease at the edge's starting node. To learn these probabilities, we draw Markov chain Monte Carlo samples from the likelihood of a dataset (686 OPSCC patients) from three institutions. We compute the model evidence using thermodynamic integration for different graphs to determine which describes the data best.The graph maximizing the model evidence connects the tumor to each LNL and the LNLs I through V in order. It predicts the risk of occult disease in level IV is below 5% if level III is clinically negative, and that the risk of occult disease in level V is below 5% except for advanced T-category (T3 and T4) patients with clinical involvement of levels II, III, and IV. The provided statistical model of nodal involvement in OPSCC patients trained on multi-institutional data may guide the design of clinical trials on volume-deescalated treatment of OPSCC and contribute to more personal guidelines on elective nodal treatment.

A multi-centric dataset on patient-individual pathological lymph node involvement in head and neck squamous cell carcinoma.

Dataset: We provide a dataset on lymph node metastases in 968 patients with newly diagnosed head and neck squamous cell carcinoma (HNSCC). All patients received neck dissection and we report the number of metastatic versus investigated lymph nodes per lymph node level (LNL) for every individual patient. Additionally, clinicopathological factors including T-category, primary tumor subsite (ICD-O-3 code), age, and sex are reported for all patients. The data is provided as three datasets: Dataset 1 contains 373 HNSCC patients treated at Centre Léon Bérard (CLB), France, with primary tumor location in the oral cavity, oropharynx, hypopharynx, and larynx. Dataset 2 contains 332 HNSCC patients treated at the Inselspital, Bern University Hospital (ISB), Switzerland with primary tumor location in the oral cavity, oropharynx, hypopharynx, and larynx. For these patients, additional information is provided including lateralization of the primary tumor, size and location of the largest metastases, and clinical involvement based on computed tomography (CT), magnetic resonance imaging (MRI), and/or 18FDG-positron emission tomography (PET/CT) imaging. Dataset 3 consists of 263 oropharyngeal SCC patients underlying a previous publication by Bauwens et al. [1], which were treated at CLB. For these patients, additional information including HPV status, lateralization of the primary tumor and clinically diagnosed lymph node involvement is provided. Reuse Potential: The data may be used to quantify the probability of occult lymph node metastases in each LNL, depending on an individual patient's characteristics of the primary tumor and the location of clinically diagnosed lymph node metastases. As such, the data may contribute to further personalize the elective treatment of the neck for HNSCC patients, i.e. definition of the elective clinical target volume (CTV-N) in radiotherapy (RT) and the extent of neck dissection (ND) in surgery. There exists only one similar publicly available dataset that reports clinical involvement per LNL in 287 oropharyngeal SCC patients [2]. The data presented in this article substantially extends the available data, it additionally includes pathologically assessed involvement per LNL, and it provides data for multiple subsites in the head and neck region.