Tumor Growth Kinetics and the Biological Cost of Treatment Delay in Oral Cancer

Tumor Growth Kinetics and the Biological Cost of Treatment Delay in Oral Cancer | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Tumor Growth Kinetics and the Biological Cost of Treatment Delay in Oral Cancer Arjun Gurmeet Singh, Abhishek Mahajan, Shwetabh Sinha, Rathan Shetty, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7855507/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This prospective cohort study quantified the biological impact of treatment delay in oral squamous cell carcinoma (OSCC) through tumour kinetics. Between July 2020 and December 2023, 483 patients with treatment-naïve OSCC, Mumbai, underwent two pre-surgery cross-sectional imaging studies at least three weeks apart. Gross tumour volume (GTV) was measured to calculate weekly percentage growth and tumour volume doubling time (TVDT) using the Schwartz exponential model. The median interval between scans was 7.1 weeks (IQR, 5.9–9.4). Median GTV increased from 12.9 cm³ (IQR, 8.1–20.2) to 19.4 cm³ (IQR, 12.3–28.6), a 7.3% median weekly rise corresponding to a TVDT of 7.9 weeks. Tongue tumours grew fastest (9.6% per week; TVDT 6.2 weeks). Stage migration occurred in 30%, leading to more extensive resections in 28%. At 25 months’ median follow-up, 2-year overall survival (OS) and disease-specific survival were 67% and 73%, respectively. Patients with TVDT ≤8 weeks had lower OS (58% vs 74%, p=0.002). On multivariable analysis, TVDT ≤8 weeks, treatment delay >8 weeks, advanced T/N-category, and perineural invasion independently predicted worse outcomes. OSCC doubles in volume within 6–10 weeks, and tumour kinetics offer a quantifiable marker of aggressiveness that should inform scheduling and prognosis. Biological sciences/Cancer Health sciences/Oncology Oral cancer tumour volume natural progression AJCC classification treatment delay Figures Figure 1 Figure 2 Introduction Oral squamous cell carcinoma (OSCC) constitutes over 90% of all oral cavity malignancies and remains one of the most common cancers in South and Southeast Asia, with India alone contributing nearly one-third of the global burden.( 1 , 2 ) Despite the ease of access for visual inspection, OSCC is frequently diagnosed at advanced stages, leading to persistently low survival rates of around 50%.( 3 , 4 ) This underscores the urgent need to refine prognostic assessment beyond conventional TNM staging and identify factors that reflect true biological behaviour. Tumour volume has emerged as an important prognostic biomarker. Multiple studies demonstrate that volumetric measurements outperform linear dimensions and add prognostic value even within the same TNM categories. ( 5 ) Larger volumes are consistently associated with higher recurrence rates, treatment failure, and inferior survival, including in patients classified as early-stage by AJCC.( 5 ) Additional histopathologic features such as perineural invasion (PNI), lymphovascular invasion (LVI), depth of invasion (DOI), and worst pattern of invasion (WPOI) also predict poorer outcomes and now guide adjuvant therapy decisions in early OSCC. ( 6 – 10 ) Time to treatment initiation (TTI) has been highlighted as another critical prognostic factor. Delays of more than six to eight weeks between diagnosis and definitive therapy are associated with worse disease control and overall survival across head and neck subsites.( 11 , 12 ) In clinical practice, however, delays may arise from both patient-driven factors (fear of surgery, financial or social barriers, search for alternative treatments) and system-level constraints (referral bottlenecks, long surgical waiting lists, competing resource demands).( 13 ) In high-volume public health systems, where patient loads exceed capacity, such delays are often unavoidable and contribute to tumour progression, stage migration, and ultimately poorer outcomes.( 14 ) Patients themselves frequently ask about the “safe” window before surgery, yet clinicians lack robust prospective data to guide counselling. The biological implications of treatment delay remain less explored. While clinicians recognize that verrucous or exophytic tumours often progress slower compared to ulcerative or infiltrative lesions, there is limited evidence quantifying growth kinetics across subsites or histological grades. AJCC 8th edition refined staging with the addition of DOI and extranodal extension, but these static measures cannot capture dynamic tumour growth. Tumour kinetics—particularly volumetric growth rate and tumour volume doubling time (TVDT)—may provide critical insight into real-time tumour biology and its impact on stage migration and survival. Against this background, we conducted a prospective clinical study at a high-volume tertiary cancer centre to systematically evaluate tumour growth kinetics, TVDT, stage migration, and patterns of spread in treatment-naïve OSCC during diagnostic and treatment delays. By correlating these kinetics with survival outcomes, we aimed to determine whether tumour progression provides independent prognostic information beyond established clinicopathological variables and AJCC staging. Material and Methods Study Design and Population This was a single-centre, prospective observational cohort study conducted at the Head and Neck Disease Management Group, Tata Memorial Centre, Mumbai, between July 2020 and December 2023. Ethical approval was obtained from the institutional review board. All research was performed in accordance with relevant guidelines/regulations and obtaining patient consents from all participants. The study followed STROBE reporting guidelines, and a participant flow diagram is provided (Figure S1 ). Of 677 patients screened, 194 (28.7%) were excluded: 82 progressed to unresectable disease, 46 defaulted before treatment, 39 were unfit due to comorbidities, and 27 were lost to follow-up. The final cohort comprised 483 patients (71.3%) who completed definitive surgery and adjuvant therapy as indicated. Eligible patients were adults (18–75 years) with histologically confirmed, treatment-naïve invasive squamous cell carcinoma of the oral cavity who were planned for curative-intent surgical resection. Inclusion required availability of at least two pre-treatment cross-sectional imaging studies—contrast-enhanced CT, MRI, or PET-CT—performed approximately 3 weeks or more apart, prior to surgery. Patients were enrolled prospectively at the time of their second presentation when repeat or confirmatory imaging was obtained for final treatment planning. Exclusion criteria were prior treatment to the head and neck region, recurrent disease, or lack of adequate imaging. Imaging Acquisition and Analysis In-house imaging was performed using GE Light Speed VCT scanners with standardized protocols: field of view from frontal sinus to root of neck, 512×512 resolution, 1 mm slice thickness, 24×1.2 mm collimation, and 0.45 pitch. Intravenous contrast was administered per body weight. For scans performed outside the institute, Digital Imaging and Communications in Medicine (DICOM) files were uploaded into the hospital PACS system and reviewed for adequacy. If only axial series were available, coronal and sagittal planes were reconstructed. Volumetric Measurements Gross tumor volume (GTV) was manually contoured by a radiologist and head and neck surgeon/clinician using Eclipse v16 (Varian Medical Systems). Tumour and largest nodal metastasis (if present) were segmented in axial, coronal, and sagittal planes. Volumes were computed by the software. Suspicious nodes were defined by standard radiologic criteria: short-axis > 10 mm, ill-defined margins, capsular enhancement, or central necrosis. Tumour volume doubling time (TVDT) was calculated using the Schwartz formula: \(\:TVDT=\frac{t\times\:\text{l}\text{n}\left(2\right)}{\text{l}\text{n}({V}_{2}/{V}_{1})}\) , where t is the time interval in weeks, and V1 and V2 are baseline and follow-up GTVs. Growth rate was also expressed as percentage increase per week. Radiographic Tumour Thickness and Depth of Invasion Orthogonal diameters (anterior-posterior, medio-lateral, cranio-caudal) and radiographic tumor thickness (RTT) were measured using PACS software. RTT was defined as the perpendicular distance from adjacent normal mucosa to the deepest visible tumor extent. For survival analysis, pathological depth of invasion (DOI) was used from surgical specimens, in line with AJCC 8th edition definitions. RTT is reported separately, acknowledging that radiologic thickness has not been uniformly validated against pathological DOI in OSCC. Stage Migration and Patterns of Spread Tumour progression was documented as changes in T-category and N-category between baseline and follow-up imaging, using AJCC 8th edition criteria. Overall TNM stage was reassigned accordingly. Nodal changes were further subclassified into N0→N1, N1→N2a/b/c, and presence of extranodal extension (ENE). Radiographic ENE was defined by capsular irregularity and infiltration into surrounding fat planes, while pathologic ENE was confirmed on histology. Spread into adjacent structures (alveolus, buccinator, masticator space, infratemporal fossa, retroantral space, bone, midline tongue) was also documented per subsite. Treatment Delay and Outcomes Treatment delay was defined as the interval between diagnostic biopsy and definitive surgery. Patients were stratified into ≤ 8 weeks vs > 8 weeks, consistent with prior literature. Delay between surgery and adjuvant therapy initiation was also recorded. The primary endpoints were tumor growth kinetics (GTV change, TVDT), stage migration, and nodal progression. Secondary endpoints were overall survival (OS), disease-specific survival (DSS), and recurrence patterns (local, regional, distant). Statistical Analysis All data were entered in Microsoft Excel and analysed using SPSS v28 (IBM, Armonk, NY). Continuous variables are reported as medians with interquartile ranges (IQR) and ranges. Categorical variables are reported as frequencies and percentages with numerators/denominators. Kaplan–Meier curves were generated for OS and DSS, and differences compared by log-rank tests. Cox proportional hazards regression identified independent predictors of OS and DSS; hazard ratios (HR) and 95% confidence intervals (CI) are reported. A two-sided p < 0.05 was considered statistically significant. Results Patient Characteristics A total of 677 patients were screened between July 2020 and December 2023, of whom 483 (71.3%) completed definitive treatment and were included in the analysis. The median age was 55 years (IQR 48–62, range 19–75), with a male-to-female ratio of 3.2:1. The most common primary subsites were buccal mucosa (n = 189/483, 39%) and tongue (n = 179/483, 37%), followed by alveolus (n = 58/483, 12%), retromolar trigone (n = 38/483, 8%), and hard palate (n = 19/483, 4%). At baseline, 101 patients (21%) were staged as T1, 155 (32%) as T2, 134 (28%) as T3, and 93 (19%) as T4. In terms of nodal status, 261 (54%) were N0, 141 (29%) N1, and 81 (17%) N2+. Nearly one-fifth of patients had comorbidities such as diabetes or hypertension, and 14% reported weight loss greater than 10% at presentation, reflecting systemic effects of advanced disease. Tumour Growth Kinetics The median interval between baseline and follow-up imaging was 7.1 weeks (IQR 5.9–9.4, range 3–14). Median baseline gross tumor volume (GTV) was 12.9 cm³ (IQR 8.1–20.2; range 3.0–52.6), which increased to 19.4 cm³ (IQR 12.3–28.6; range 4.8–69.2) at follow-up. This corresponded to a median growth rate of 7.3% per week (IQR 5.6–9.1). The calculated tumor volume doubling time (TVDT) was 7.9 weeks (IQR 6.4–10.8). Tongue primaries showed the fastest growth at 9.6% per week (TVDT 6.2 weeks), followed by buccal mucosa at 6.4% per week (TVDT 9.1 weeks) and alveolus at 5.8% per week (TVDT 9.6 weeks). Poorly differentiated tumours grew at 10.4% per week (TVDT 6.0 weeks), compared to moderately differentiated (7.5% per week, TVDT 8.2 weeks) and well-differentiated tumours (6.1% per week, TVDT 9.4 weeks). Patients with perineural invasion (PNI, 71/483, 15%) had significantly higher baseline volumes (median 20.3 cm³ vs 11.8 cm³, p = 0.02) and shorter TVDTs (7.0 weeks vs 8.3 weeks). When projected clinically, these kinetics equate to an approximate doubling of tumor size within 2 months, particularly in tongue and poorly differentiated tumours. Stage Migration T-category progression was observed in 37/101 (37%) of T1 lesions, which upstaged to T2 or higher; 68/155 (44%) of T2 lesions progressed to T3 or T4; and 55/134 (41%) of T3 lesions advanced to T4. (Table 1 ) Tongue tumours were most aggressive, with nearly half of T2 lesions upstaging to T3 within three months. Patients with alveolar tumours were more likely to show early bone involvement, while buccal mucosa primaries demonstrated lateral extension before deeper invasion. Nodal progression occurred in 112/483 patients (23%). Of the 261 patients who were N0 at baseline, 60 (23%) developed nodal disease: 42 progressed to N1, 13 to N2a/b, and 5 to N2c. Among 141 patients staged N1 at baseline, 52 (37%) advanced to N2 disease, and ENE was suspected radiographically in 9 patients (6%), of whom 6 (4%) were pathologically confirmed. Patients with baseline N2 disease (81/483, 17%) demonstrated further increases in nodal size and necrosis in 34 cases (42%), although most remained in the same N-category. Overall, stage migration (T and/or N) was documented in 146 patients (30%). Importantly, stage migration frequently translated into the need for more extensive surgery, including composite resections, segmental mandibulectomy, or free flap reconstruction, which were rarely indicated at initial presentation. Table 1: Stage migration and surgical impact of delay in seeking treatment Category Baseline (n, %) At Progression (n, %) Upstaged (n, %) Associated Surgical Escalation cT Category T1: 101 (21%) T2: 155 (32%) T3: 134 (28%) T4: 93 (19%) T1: 65 (13%) T2: 109 (23%) T3: 163 (34%) T4: 146 (30%) T1 → ≥T2: 37 (36%) T2 → ≥T3/T4: 68 (44%) T3 → T4: 55 (41%) Mandibulectomy (n = 46) Alveolus/bone resection (n = 32) Skin excision (n = 18) Extended tongue resection (n = 24) cN Category N0: 261 (54%) N1: 141 (29%) N2+: 81 (17%) N0: 201 (41%) N1: 122 (25%) N2+: 160 (33%) N0 → N+: 60 (23%) N1 → N2+: 52 (37%) Extended neck dissection (n = 38) Overall Stage (AJCC 8th) I: 89 (18%) II: 173 (36%) III: 126 (26%) IV: 95 (20%) I: 61 (13%) II: 127 (26%) III: 145 (30%) IV: 150 (31%) Overall upstaged: 147 (30%) Combined resections and/or adjuvant chemoradiotherapy increased Patterns of Spread Local progression was evident in 454/483 patients (94%). Tongue tumours extended predominantly in the antero-posterior axis (111/179, 62%), with only 38/179 (21%) crossing the midline within the 2–3-month interval, suggesting initial containment by midline raphe. Buccal mucosa primaries extended into adjacent alveolus in 76/189 cases (40%) and into the masticator space in 29/189 (15%). Bone erosion was observed in 91/483 patients (19%), predominantly among alveolar and retromolar lesions. Retromolar trigone tumours spread superiorly into the infratemporal fossa in 17/38 (44%) compared to 8/38 (22%) extending anteriorly. Retroantral space involvement was identified in 48/483 patients (10%) and was associated with faster growth rates (median 11% per week vs 7% per week, p = 0.01). These data highlight subsite-specific patterns of spread, with tongue tumours favouring longitudinal extension, buccal tumours spreading laterally, and RMT lesions progressing superiorly. Survival Outcomes At a median follow-up of 25 months (IQR 18–33, range 14–44), the 2-year overall survival (OS) was 67% (95% CI 62–71%), and disease-specific survival (DSS) was 73% (95% CI 68–77%). Treatment delay > 8 weeks was associated with inferior 2-year OS (55% vs 75%; HR 1.6, 95% CI 1.1–2.3, p = 0.02). Patients with larger baseline tumor volumes (> 15 cm³) also had worse OS (58% vs 72%; HR 1.5, 95% CI 1.0–2.2, p = 0.03). On subgroup analysis, patients with TVDT ≤ 8 weeks (n = 244) had a 2-year OS of 58% compared to 74% in those with TVDT > 8 weeks (n = 239) (log-rank p = 0.002). (Table 2 ) This effect was observed both in early-stage disease (Stage I–II: 68% vs 81%) and advanced-stage disease (Stage III–IV: 48% vs 61%). Multivariate Cox regression confirmed that TVDT ≤ 8 weeks, treatment delay > 8 weeks, advanced T-category, nodal positivity, and PNI were independent predictors of OS. DSS showed a similar pattern, with high-volume and rapidly growing tumours faring significantly worse. Patterns of recurrence included local (17%), regional (13%), and distant metastases (7%), with higher recurrence rates in the short-TVDT group. (Fig. 2 a and b) Table 2 Prognostic factors impacting 2-year overall survival Variable Groups (n) 2-Year OS (%) Log-Rank p-Value Multivariable HR (95% CI) p-Value Tumor site Tongue (179) vs Buccal mucosa (189) 61 vs 69 0.07 1.2 (0.9–1.6) 0.11 Tumor volume ≤ 15 cm³ (246) vs > 15 cm³ (237) 72 vs 58 0.03 1.5 (1.1–2.0) 0.03 Treatment delay (TTI) ≤ 8 weeks (274) vs > 8 weeks (209) 75 vs 55 0.02 1.6 (1.1–2.3) 0.02 pT category T1–2 (254) vs T3–4 (229) 78 vs 52 < 0.001 1.8 (1.3–2.5) < 0.001 pN category N0 (261) vs N+ (222) 74 vs 56 10 mm (215) 73 vs 59 0.01 1.4 (1.0–1.9) 0.04 Perineural invasion Absent (412) vs Present (71) 70 vs 49 0.01 1.5 (1.0–2.2) 0.04 Lymphovascular invasion Absent (435) vs Present (48) 69 vs 47 0.02 1.4 (0.9–2.1) 0.07 Worst pattern of invasion (WPOI) 1–3 (308) vs 4–5 (175) 72 vs 53 < 0.001 1.6 (1.2–2.2) 0.002 Stage migration No (336) vs Yes (147) 71 vs 55 0.01 1.5 (1.1–2.1) 0.02 Discussion This prospective study provides one of the most comprehensive evaluations to date of the natural progression and tumor kinetics of oral squamous cell carcinoma (OSCC) using serial imaging. By integrating volumetric data, doubling time analysis, and stage migration with survival outcomes in a large cohort of 483 patients, we demonstrate that OSCC exhibits biologically aggressive progression even over short treatment delays. The median tumor volume doubling time (TVDT) ranged from 6–10 weeks, with tongue primaries and poorly differentiated tumours growing most rapidly. These findings have both biological and practical implications, highlighting the importance of timely intervention and the potential role of volumetric kinetics as an independent prognostic variable. Treatment delay has long been recognized as detrimental in head and neck cancers, yet its biological underpinning has rarely been quantified. Most prior studies are retrospective, administrative, or population-based, relying on registry data that link delays to survival but without validating whether measurable disease progression occurs during that interval. ( 12 – 15 ) The present study bridges that gap, prospectively documenting tangible volumetric growth and stage migration during pre-treatment waiting periods. The observed median growth rate of 7.3% per week, corresponding to near doubling within two months, mirrors theoretical models proposed by Schwartz and colleagues for exponential tumor kinetics. ( 17 , 18 ) This rate of progression underscores that OSCC is far from indolent; even modest delays can have clinically meaningful consequences for resectability and prognosis. Our findings affirm earlier reports that tumor volume and treatment delay independently influence outcomes. ( 13 , 19 ) However, by explicitly calculating TVDT, we demonstrate a quantifiable biological parameter that links these two phenomena. Patients with TVDT ≤ 8 weeks had nearly 16% lower two-year overall survival and a 1.7-fold higher risk of death independent of T-category, N-category, or perineural invasion. These data suggest that tumor kinetics capture an element of intrinsic aggressiveness not reflected in static TNM classification. Incorporating volumetric progression and TVDT into future staging or prognostic models could therefore improve risk stratification and guide personalized treatment scheduling. Distinct subsite-specific patterns of spread were evident and reinforce known anatomic pathways. Tongue tumours predominantly extended along the antero-posterior axis, with only one-fifth crossing the midline over two to three months, consistent with the restraining effect of the midline raphe. Buccal mucosa lesions expanded laterally into the alveolus and masticator space, while retromolar trigone tumours favoured superior extension into the infratemporal fossa. Retroantral space involvement, though less common, was linked to significantly accelerated growth rates. These observations emphasize the heterogeneity of OSCC behaviour and have practical implications for preoperative imaging, surgical planning, and adjuvant field delineation. ( 7 , 8 , 23 ) The phenomenon of stage migration in this cohort—observed in nearly one-third of patients—translated directly into changes in management. Patients who were initially operable with limited resections often required more extensive composite resections, segmental mandibulectomy, or free-flap reconstruction after interval progression. In certain cases, progression rendered disease unresectable. Thus, treatment delay not only worsens survival but also increases surgical morbidity, functional impairment, and economic burden. ( 6 , 9 , 21 ) These findings reinforce the need for institutional protocols that prioritize surgical scheduling based on tumor kinetics rather than chronological order alone. The concept of TVDT offers a dynamic, easily interpretable metric of tumor aggressiveness. It allows clinicians to estimate the biological impact of delay using a quantifiable measure rather than intuition alone. A shorter TVDT reflects high proliferative potential, possibly related to underlying molecular events such as p53 mutations, EGFR overexpression, or hypoxia-inducible signalling, which warrant further investigation. ( 16 , 20 ) Future multi-institutional studies could explore the molecular correlates of radiologically derived TVDT, establishing it as a surrogate imaging biomarker of aggressiveness in OSCC. Our analysis also illustrates that tumor growth is not strictly linear. Although we calculated weekly percentage changes and doubling times assuming uniform growth for practicality, the biological reality is likely nonlinear, with an early exponential phase followed by a plateau. The relatively short observation intervals (median seven weeks) minimize this deviation, but future work using serial imaging at multiple points could refine kinetic modelling further. ( 5 , 18 ) A notable methodological feature of this study is the deliberate separation of radiographic and pathologic parameters. Radiographic tumor thickness (RTT) and radiologic extranodal extension (rENE) were recorded objectively but interpreted cautiously, acknowledging that these measures have not been uniformly validated against pathology in OSCC. ( 9 , 10 , 24 ) Pathologic depth of invasion (DOI) and ENE, where available, were used for prognostication. RTT nonetheless offers a pragmatic alternative in preoperative settings, providing a reproducible measure to track interim progression. A strong correlation between RTT and DOI, once established prospectively, could make imaging-derived metrics invaluable for dynamic risk assessment. The limitations of the current study include: (i) although prospectively designed, it represents experience from a single high-volume cancer centre, which may limit generalizability; (ii) despite standardized imaging protocols, minor variations in contrast timing, slice reconstruction, and contouring could influence volumetric accuracy; (iii) approximately 12% of screened patients who progressed to unresectable disease before definitive treatment were excluded from survival analyses, possibly underestimating the full impact of delay; (iv) radiologic parameters such as RTT and rENE require further validation against pathologic gold standards; (v) our modelling assumes linear growth between imaging points, which may simplify complex biological kinetics. Despite these limitations, the strengths of this work are significant. It is one of the largest prospective datasets to examine tumor kinetics in OSCC, employs standardized contouring by a multidisciplinary team, and integrates volumetric kinetics with survival endpoints. The study provides direct biological evidence for the clinical observation that OSCC can change substantially over short intervals. Treatment delay should not be viewed merely as a logistical constraint but as a biological and systemic issue. In public tertiary centres, delays arise from both patient-related factors—financial limitations, social obligations, treatment hesitancy—and system-level constraints such as overburdened operating schedules, limited surgical slots, and pandemic-era backlogs. Our findings quantify the biological cost of these delays: even an additional month between diagnosis and surgery can result in measurable tumor volume increase, stage migration, and compromised survival. In contexts where complete elimination of delay is unrealistic, triaging based on biological risk—such as high-volume, short-TVDT tumours—may help allocate limited resources most effectively. Future directions include multicentric validation, incorporation of MRI-based radiomics for microstructural assessment, and exploration of whether kinetic metrics can predict treatment response or recurrence patterns. ( 22 , 25 , 26 ) OSCC exhibits rapid volumetric progression, with tumours doubling in size within 6–10 weeks. Shorter tumor volume doubling time, advanced stage, and treatment delay beyond eight weeks independently predict poorer survival. Tumour kinetics thus serve as a dynamic biomarker that transcends static staging, offering actionable information for clinicians and policymakers. Integrating TVDT and volumetric growth into prognostic frameworks could improve patient counselling, surgical prioritization, and health system planning. At a broader level, this study reinforces the urgent need for institutional and policy-level strategies to minimize diagnostic and treatment delays, thereby improving both survival and quality of life in patients with oral cancer. Declarations Funding statement Nil. No funding was obtained from any sources. Conflict of Interest statement Nil. None of the authors have any conflict of interest to declare. Ethics Approval Statement This study has been approved by the Institutional Ethics Committee Data Availability Statement Data will not be made available as per the Institute’s Ethic Committee Approval letter Authors contribution statement Dr. Arjun Gurmeet Singh (Corresponding author)*: Study concept, design, data collection and analysis, manuscript drafting and revision Dr. Abhishek Mahajan: Study concept, design, data analysis, manuscript drafting and revision Dr. Shwetabh Sinha: Data collection and analysis, manuscript drafting and revision Dr. Rathan Shetty: Data collection and analysis, manuscript drafting and revision Dr. Samarprita Mohanty: Data collection and analysis, manuscript drafting and revision Dr. Anuj Kumar: Data collection and analysis, manuscript drafting and revision Dr. Nivedita Chakrabarty: Data analysis, manuscript drafting and revision Dr. Poonam Joshi: Manuscript drafting and revision Dr. Sudhir Nair: Manuscript drafting and revision Dr. Sarbani Ghosh Laskar: Manuscript drafting and revision Dr. Kumar Prabhash: Manuscript drafting and revision Dr. Pankaj Chaturvedi: Study concept, design, data collection and analysis, manuscript drafting and revision References Ferlay, J. et al. in Global Cancer Observatory: Cancer Today . 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External validation of a prognostic radiomic signature in head and neck squamous cell carcinoma. Radiother Oncol. 117 (3), 427–432 (2015). Additional Declarations No competing interests reported. Supplementary Files SupplementaryFigure1.jpg Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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07:10:03","extension":"html","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":98049,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7855507/v1/fad0708014059d8680241a6f.html"},{"id":95894877,"identity":"353e583f-dcd9-43ae-a0d9-8a08287d3521","added_by":"auto","created_at":"2025-11-14 07:10:02","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1096106,"visible":true,"origin":"","legend":"\u003cp\u003eSite-specific volumetric progression of tumor over time\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7855507/v1/aab4ab916e61c059039241d2.jpg"},{"id":95894893,"identity":"3fbdfb36-aa48-44b9-baf7-ef7d001aea99","added_by":"auto","created_at":"2025-11-14 07:10:03","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":3392386,"visible":true,"origin":"","legend":"\u003cp\u003ea and 2b: Overall Survival (a) and Disease Specific Survival (b) plots showing differences in stage and tumor volume, with number at risk\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7855507/v1/b85489e8211b688af76217ff.png"},{"id":98775069,"identity":"7e0b3cc4-c35d-4e22-ba29-77c0ef789069","added_by":"auto","created_at":"2025-12-22 12:18:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4506761,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7855507/v1/3d6e1611-3779-45d1-aa32-8717dc48001b.pdf"},{"id":95894876,"identity":"2253d1f3-2600-4130-821d-82299f932a24","added_by":"auto","created_at":"2025-11-14 07:10:02","extension":"jpg","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":111266,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7855507/v1/fb304a2b4ebd57a6ba1444c0.jpg"}],"financialInterests":"No competing interests reported.","formattedTitle":"Tumor Growth Kinetics and the Biological Cost of Treatment Delay in Oral Cancer","fulltext":[{"header":"Introduction","content":"\u003cp\u003e Oral squamous cell carcinoma (OSCC) constitutes over 90% of all oral cavity malignancies and remains one of the most common cancers in South and Southeast Asia, with India alone contributing nearly one-third of the global burden.(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) Despite the ease of access for visual inspection, OSCC is frequently diagnosed at advanced stages, leading to persistently low survival rates of around 50%.(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) This underscores the urgent need to refine prognostic assessment beyond conventional TNM staging and identify factors that reflect true biological behaviour.\u003c/p\u003e\u003cp\u003eTumour volume has emerged as an important prognostic biomarker. Multiple studies demonstrate that volumetric measurements outperform linear dimensions and add prognostic value even within the same TNM categories. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) Larger volumes are consistently associated with higher recurrence rates, treatment failure, and inferior survival, including in patients classified as early-stage by AJCC.(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) Additional histopathologic features such as perineural invasion (PNI), lymphovascular invasion (LVI), depth of invasion (DOI), and worst pattern of invasion (WPOI) also predict poorer outcomes and now guide adjuvant therapy decisions in early OSCC. (\u003cspan additionalcitationids=\"CR7 CR8 CR9\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eTime to treatment initiation (TTI) has been highlighted as another critical prognostic factor. Delays of more than six to eight weeks between diagnosis and definitive therapy are associated with worse disease control and overall survival across head and neck subsites.(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) In clinical practice, however, delays may arise from both patient-driven factors (fear of surgery, financial or social barriers, search for alternative treatments) and system-level constraints (referral bottlenecks, long surgical waiting lists, competing resource demands).(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) In high-volume public health systems, where patient loads exceed capacity, such delays are often unavoidable and contribute to tumour progression, stage migration, and ultimately poorer outcomes.(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) Patients themselves frequently ask about the \u0026ldquo;safe\u0026rdquo; window before surgery, yet clinicians lack robust prospective data to guide counselling.\u003c/p\u003e\u003cp\u003eThe biological implications of treatment delay remain less explored. While clinicians recognize that verrucous or exophytic tumours often progress slower compared to ulcerative or infiltrative lesions, there is limited evidence quantifying growth kinetics across subsites or histological grades. AJCC 8th edition refined staging with the addition of DOI and extranodal extension, but these static measures cannot capture dynamic tumour growth. Tumour kinetics\u0026mdash;particularly volumetric growth rate and tumour volume doubling time (TVDT)\u0026mdash;may provide critical insight into real-time tumour biology and its impact on stage migration and survival.\u003c/p\u003e\u003cp\u003eAgainst this background, we conducted a prospective clinical study at a high-volume tertiary cancer centre to systematically evaluate tumour growth kinetics, TVDT, stage migration, and patterns of spread in treatment-na\u0026iuml;ve OSCC during diagnostic and treatment delays. By correlating these kinetics with survival outcomes, we aimed to determine whether tumour progression provides independent prognostic information beyond established clinicopathological variables and AJCC staging.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design and Population\u003c/h2\u003e\u003cp\u003eThis was a single-centre, prospective observational cohort study conducted at the Head and Neck Disease Management Group, Tata Memorial Centre, Mumbai, between July 2020 and December 2023. Ethical approval was obtained from the institutional review board. All research was performed in accordance with relevant guidelines/regulations and obtaining patient consents from all participants. The study followed STROBE reporting guidelines, and a participant flow diagram is provided (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Of 677 patients screened, 194 (28.7%) were excluded: 82 progressed to unresectable disease, 46 defaulted before treatment, 39 were unfit due to comorbidities, and 27 were lost to follow-up. The final cohort comprised 483 patients (71.3%) who completed definitive surgery and adjuvant therapy as indicated.\u003c/p\u003e\u003cp\u003eEligible patients were adults (18\u0026ndash;75 years) with histologically confirmed, treatment-na\u0026iuml;ve invasive squamous cell carcinoma of the oral cavity who were planned for curative-intent surgical resection. Inclusion required availability of at least two pre-treatment cross-sectional imaging studies\u0026mdash;contrast-enhanced CT, MRI, or PET-CT\u0026mdash;performed approximately 3 weeks or more apart, prior to surgery. Patients were enrolled prospectively at the time of their second presentation when repeat or confirmatory imaging was obtained for final treatment planning. Exclusion criteria were prior treatment to the head and neck region, recurrent disease, or lack of adequate imaging.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eImaging Acquisition and Analysis\u003c/h3\u003e\n\u003cp\u003eIn-house imaging was performed using GE Light Speed VCT scanners with standardized protocols: field of view from frontal sinus to root of neck, 512\u0026times;512 resolution, 1 mm slice thickness, 24\u0026times;1.2 mm collimation, and 0.45 pitch. Intravenous contrast was administered per body weight. For scans performed outside the institute, Digital Imaging and Communications in Medicine (DICOM) files were uploaded into the hospital PACS system and reviewed for adequacy. If only axial series were available, coronal and sagittal planes were reconstructed.\u003c/p\u003e\n\u003ch3\u003eVolumetric Measurements\u003c/h3\u003e\n\u003cp\u003eGross tumor volume (GTV) was manually contoured by a radiologist and head and neck surgeon/clinician using Eclipse v16 (Varian Medical Systems). Tumour and largest nodal metastasis (if present) were segmented in axial, coronal, and sagittal planes. Volumes were computed by the software. Suspicious nodes were defined by standard radiologic criteria: short-axis\u0026thinsp;\u0026gt;\u0026thinsp;10 mm, ill-defined margins, capsular enhancement, or central necrosis. Tumour volume doubling time (TVDT) was calculated using the Schwartz formula: \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:TVDT=\\frac{t\\times\\:\\text{l}\\text{n}\\left(2\\right)}{\\text{l}\\text{n}({V}_{2}/{V}_{1})}\\)\u003c/span\u003e\u003c/span\u003e, where t is the time interval in weeks, and V1 and V2 are baseline and follow-up GTVs. Growth rate was also expressed as percentage increase per week.\u003c/p\u003e\n\u003ch3\u003eRadiographic Tumour Thickness and Depth of Invasion\u003c/h3\u003e\n\u003cp\u003eOrthogonal diameters (anterior-posterior, medio-lateral, cranio-caudal) and radiographic tumor thickness (RTT) were measured using PACS software. RTT was defined as the perpendicular distance from adjacent normal mucosa to the deepest visible tumor extent. For survival analysis, pathological depth of invasion (DOI) was used from surgical specimens, in line with AJCC 8th edition definitions. RTT is reported separately, acknowledging that radiologic thickness has not been uniformly validated against pathological DOI in OSCC.\u003c/p\u003e\n\u003ch3\u003eStage Migration and Patterns of Spread\u003c/h3\u003e\n\u003cp\u003eTumour progression was documented as changes in T-category and N-category between baseline and follow-up imaging, using AJCC 8th edition criteria. Overall TNM stage was reassigned accordingly. Nodal changes were further subclassified into N0\u0026rarr;N1, N1\u0026rarr;N2a/b/c, and presence of extranodal extension (ENE). Radiographic ENE was defined by capsular irregularity and infiltration into surrounding fat planes, while pathologic ENE was confirmed on histology. Spread into adjacent structures (alveolus, buccinator, masticator space, infratemporal fossa, retroantral space, bone, midline tongue) was also documented per subsite.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eTreatment Delay and Outcomes\u003c/h2\u003e\u003cp\u003eTreatment delay was defined as the interval between diagnostic biopsy and definitive surgery. Patients were stratified into \u0026le;\u0026thinsp;8 weeks vs\u0026thinsp;\u0026gt;\u0026thinsp;8 weeks, consistent with prior literature. Delay between surgery and adjuvant therapy initiation was also recorded. The primary endpoints were tumor growth kinetics (GTV change, TVDT), stage migration, and nodal progression. Secondary endpoints were overall survival (OS), disease-specific survival (DSS), and recurrence patterns (local, regional, distant).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eAll data were entered in Microsoft Excel and analysed using SPSS v28 (IBM, Armonk, NY). Continuous variables are reported as medians with interquartile ranges (IQR) and ranges. Categorical variables are reported as frequencies and percentages with numerators/denominators. Kaplan\u0026ndash;Meier curves were generated for OS and DSS, and differences compared by log-rank tests. Cox proportional hazards regression identified independent predictors of OS and DSS; hazard ratios (HR) and 95% confidence intervals (CI) are reported. A two-sided p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003ePatient Characteristics\u003c/h2\u003e\n \u003cp\u003eA total of 677 patients were screened between July 2020 and December 2023, of whom 483 (71.3%) completed definitive treatment and were included in the analysis. The median age was 55 years (IQR 48\u0026ndash;62, range 19\u0026ndash;75), with a male-to-female ratio of 3.2:1. The most common primary subsites were buccal mucosa (n\u0026thinsp;=\u0026thinsp;189/483, 39%) and tongue (n\u0026thinsp;=\u0026thinsp;179/483, 37%), followed by alveolus (n\u0026thinsp;=\u0026thinsp;58/483, 12%), retromolar trigone (n\u0026thinsp;=\u0026thinsp;38/483, 8%), and hard palate (n\u0026thinsp;=\u0026thinsp;19/483, 4%). At baseline, 101 patients (21%) were staged as T1, 155 (32%) as T2, 134 (28%) as T3, and 93 (19%) as T4. In terms of nodal status, 261 (54%) were N0, 141 (29%) N1, and 81 (17%) N2+. Nearly one-fifth of patients had comorbidities such as diabetes or hypertension, and 14% reported weight loss greater than 10% at presentation, reflecting systemic effects of advanced disease.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eTumour Growth Kinetics\u003c/h2\u003e\n \u003cp\u003eThe median interval between baseline and follow-up imaging was 7.1 weeks (IQR 5.9\u0026ndash;9.4, range 3\u0026ndash;14). Median baseline gross tumor volume (GTV) was 12.9 cm\u0026sup3; (IQR 8.1\u0026ndash;20.2; range 3.0\u0026ndash;52.6), which increased to 19.4 cm\u0026sup3; (IQR 12.3\u0026ndash;28.6; range 4.8\u0026ndash;69.2) at follow-up. This corresponded to a median growth rate of 7.3% per week (IQR 5.6\u0026ndash;9.1). The calculated tumor volume doubling time (TVDT) was 7.9 weeks (IQR 6.4\u0026ndash;10.8). Tongue primaries showed the fastest growth at 9.6% per week (TVDT 6.2 weeks), followed by buccal mucosa at 6.4% per week (TVDT 9.1 weeks) and alveolus at 5.8% per week (TVDT 9.6 weeks). Poorly differentiated tumours grew at 10.4% per week (TVDT 6.0 weeks), compared to moderately differentiated (7.5% per week, TVDT 8.2 weeks) and well-differentiated tumours (6.1% per week, TVDT 9.4 weeks). Patients with perineural invasion (PNI, 71/483, 15%) had significantly higher baseline volumes (median 20.3 cm\u0026sup3; vs 11.8 cm\u0026sup3;, p\u0026thinsp;=\u0026thinsp;0.02) and shorter TVDTs (7.0 weeks vs 8.3 weeks). When projected clinically, these kinetics equate to an approximate doubling of tumor size within 2 months, particularly in tongue and poorly differentiated tumours.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eStage Migration\u003c/h2\u003e\n \u003cp\u003eT-category progression was observed in 37/101 (37%) of T1 lesions, which upstaged to T2 or higher; 68/155 (44%) of T2 lesions progressed to T3 or T4; and 55/134 (41%) of T3 lesions advanced to T4. (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e) Tongue tumours were most aggressive, with nearly half of T2 lesions upstaging to T3 within three months. Patients with alveolar tumours were more likely to show early bone involvement, while buccal mucosa primaries demonstrated lateral extension before deeper invasion. Nodal progression occurred in 112/483 patients (23%). Of the 261 patients who were N0 at baseline, 60 (23%) developed nodal disease: 42 progressed to N1, 13 to N2a/b, and 5 to N2c. Among 141 patients staged N1 at baseline, 52 (37%) advanced to N2 disease, and ENE was suspected radiographically in 9 patients (6%), of whom 6 (4%) were pathologically confirmed. Patients with baseline N2 disease (81/483, 17%) demonstrated further increases in nodal size and necrosis in 34 cases (42%), although most remained in the same N-category. Overall, stage migration (T and/or N) was documented in 146 patients (30%). Importantly, stage migration frequently translated into the need for more extensive surgery, including composite resections, segmental mandibulectomy, or free flap reconstruction, which were rarely indicated at initial presentation.\u003c/p\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eTable 1: \u003cspan style=\"color:black;\"\u003eStage migration and surgical impact of delay in seeking treatment \u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003ctable style=\"border-collapse: collapse; border: none; width: 100%;\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"border: 1pt solid windowtext;padding: 0in 5.4pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eCategory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93.75pt;border-top: 1pt solid windowtext;border-right: 1pt solid windowtext;border-bottom: 1pt solid windowtext;border-image: initial;border-left: none;padding: 0in 5.4pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eBaseline (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92.15pt;border-top: 1pt solid windowtext;border-right: 1pt solid windowtext;border-bottom: 1pt solid windowtext;border-image: initial;border-left: none;padding: 0in 5.4pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eAt Progression (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120.45pt;border-top: 1pt solid windowtext;border-right: 1pt solid windowtext;border-bottom: 1pt solid windowtext;border-image: initial;border-left: none;padding: 0in 5.4pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eUpstaged (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82.5pt;border-top: 1pt solid windowtext;border-right: 1pt solid windowtext;border-bottom: 1pt solid windowtext;border-image: initial;border-left: none;padding: 0in 5.4pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eAssociated Surgical Escalation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"border-right: 1pt solid windowtext;border-bottom: 1pt solid windowtext;border-left: 1pt solid windowtext;border-image: initial;border-top: none;padding: 0in 5.4pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003ecT Category\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93.75pt;border-top: none;border-left: none;border-bottom: 1pt solid windowtext;border-right: 1pt solid windowtext;padding: 0in 5.4pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eT1: 101 (21%)\u0026nbsp;\u003c/p\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eT2: 155 (32%)\u0026nbsp;\u003c/p\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eT3: 134 (28%)\u0026nbsp;\u003c/p\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eT4: 93 (19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92.15pt;border-top: none;border-left: none;border-bottom: 1pt solid windowtext;border-right: 1pt solid windowtext;padding: 0in 5.4pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eT1: 65 (13%)\u0026nbsp;\u003c/p\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eT2: 109 (23%)\u0026nbsp;\u003c/p\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eT3: 163 (34%)\u0026nbsp;\u003c/p\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eT4: 146 (30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120.45pt;border-top: none;border-left: none;border-bottom: 1pt solid windowtext;border-right: 1pt solid windowtext;padding: 0in 5.4pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eT1 \u0026rarr; \u0026ge;T2: 37 (36%)\u0026nbsp;\u003c/p\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eT2 \u0026rarr; \u0026ge;T3/T4: 68 (44%)\u0026nbsp;\u003c/p\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eT3 \u0026rarr; T4: 55 (41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82.5pt;border-top: none;border-left: none;border-bottom: 1pt solid windowtext;border-right: 1pt solid windowtext;padding: 0in 5.4pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eMandibulectomy (n = 46) Alveolus/bone resection (n = 32) Skin excision (n = 18) Extended tongue resection (n = 24)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"border-right: 1pt solid windowtext;border-bottom: 1pt solid windowtext;border-left: 1pt solid windowtext;border-image: initial;border-top: none;padding: 0in 5.4pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003ecN Category\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93.75pt;border-top: none;border-left: none;border-bottom: 1pt solid windowtext;border-right: 1pt solid windowtext;padding: 0in 5.4pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eN0: 261 (54%)\u0026nbsp;\u003c/p\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eN1: 141 (29%)\u0026nbsp;\u003c/p\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eN2+: 81 (17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92.15pt;border-top: none;border-left: none;border-bottom: 1pt solid windowtext;border-right: 1pt solid windowtext;padding: 0in 5.4pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eN0: 201 (41%)\u0026nbsp;\u003c/p\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eN1: 122 (25%)\u0026nbsp;\u003c/p\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eN2+: 160 (33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120.45pt;border-top: none;border-left: none;border-bottom: 1pt solid windowtext;border-right: 1pt solid windowtext;padding: 0in 5.4pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eN0 \u0026rarr; N+: 60 (23%)\u0026nbsp;\u003c/p\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eN1 \u0026rarr; N2+: 52 (37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82.5pt;border-top: none;border-left: none;border-bottom: 1pt solid windowtext;border-right: 1pt solid windowtext;padding: 0in 5.4pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eExtended neck dissection (n = 38)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"border-right: 1pt solid windowtext;border-bottom: 1pt solid windowtext;border-left: 1pt solid windowtext;border-image: initial;border-top: none;padding: 0in 5.4pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eOverall Stage (AJCC 8th)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93.75pt;border-top: none;border-left: none;border-bottom: 1pt solid windowtext;border-right: 1pt solid windowtext;padding: 0in 5.4pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eI: 89 (18%)\u0026nbsp;\u003c/p\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eII: 173 (36%)\u0026nbsp;\u003c/p\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eIII: 126 (26%)\u0026nbsp;\u003c/p\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eIV: 95 (20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92.15pt;border-top: none;border-left: none;border-bottom: 1pt solid windowtext;border-right: 1pt solid windowtext;padding: 0in 5.4pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eI: 61 (13%)\u0026nbsp;\u003c/p\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eII: 127 (26%)\u0026nbsp;\u003c/p\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eIII: 145 (30%)\u0026nbsp;\u003c/p\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eIV: 150 (31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120.45pt;border-top: none;border-left: none;border-bottom: 1pt solid windowtext;border-right: 1pt solid windowtext;padding: 0in 5.4pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eOverall upstaged: 147 (30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82.5pt;border-top: none;border-left: none;border-bottom: 1pt solid windowtext;border-right: 1pt solid windowtext;padding: 0in 5.4pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;font-size:16px;font-family:\"Times New Roman\",serif;line-height:200%;'\u003eCombined resections and/or adjuvant chemoradiotherapy increased\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003ePatterns of Spread\u003c/h2\u003e\n \u003cp\u003eLocal progression was evident in 454/483 patients (94%). Tongue tumours extended predominantly in the antero-posterior axis (111/179, 62%), with only 38/179 (21%) crossing the midline within the 2\u0026ndash;3-month interval, suggesting initial containment by midline raphe. Buccal mucosa primaries extended into adjacent alveolus in 76/189 cases (40%) and into the masticator space in 29/189 (15%). Bone erosion was observed in 91/483 patients (19%), predominantly among alveolar and retromolar lesions. Retromolar trigone tumours spread superiorly into the infratemporal fossa in 17/38 (44%) compared to 8/38 (22%) extending anteriorly. Retroantral space involvement was identified in 48/483 patients (10%) and was associated with faster growth rates (median 11% per week vs 7% per week, p\u0026thinsp;=\u0026thinsp;0.01).\u003c/p\u003e\n \u003cp\u003eThese data highlight subsite-specific patterns of spread, with tongue tumours favouring longitudinal extension, buccal tumours spreading laterally, and RMT lesions progressing superiorly.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003eSurvival Outcomes\u003c/h2\u003e\n \u003cp\u003eAt a median follow-up of 25 months (IQR 18\u0026ndash;33, range 14\u0026ndash;44), the 2-year overall survival (OS) was 67% (95% CI 62\u0026ndash;71%), and disease-specific survival (DSS) was 73% (95% CI 68\u0026ndash;77%). Treatment delay\u0026thinsp;\u0026gt;\u0026thinsp;8 weeks was associated with inferior 2-year OS (55% vs 75%; HR 1.6, 95% CI 1.1\u0026ndash;2.3, p\u0026thinsp;=\u0026thinsp;0.02). Patients with larger baseline tumor volumes (\u0026gt;\u0026thinsp;15 cm\u0026sup3;) also had worse OS (58% vs 72%; HR 1.5, 95% CI 1.0\u0026ndash;2.2, p\u0026thinsp;=\u0026thinsp;0.03). On subgroup analysis, patients with TVDT\u0026thinsp;\u0026le;\u0026thinsp;8 weeks (n\u0026thinsp;=\u0026thinsp;244) had a 2-year OS of 58% compared to 74% in those with TVDT\u0026thinsp;\u0026gt;\u0026thinsp;8 weeks (n\u0026thinsp;=\u0026thinsp;239) (log-rank p\u0026thinsp;=\u0026thinsp;0.002). (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e) This effect was observed both in early-stage disease (Stage I\u0026ndash;II: 68% vs 81%) and advanced-stage disease (Stage III\u0026ndash;IV: 48% vs 61%). Multivariate Cox regression confirmed that TVDT\u0026thinsp;\u0026le;\u0026thinsp;8 weeks, treatment delay\u0026thinsp;\u0026gt;\u0026thinsp;8 weeks, advanced T-category, nodal positivity, and PNI were independent predictors of OS. DSS showed a similar pattern, with high-volume and rapidly growing tumours faring significantly worse. Patterns of recurrence included local (17%), regional (13%), and distant metastases (7%), with higher recurrence rates in the short-TVDT group. (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea and b)\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab2\" border=\"1\" class=\"fr-table-selection-hover\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePrognostic factors impacting 2-year overall survival\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGroups (n)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2-Year OS (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLog-Rank p-Value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMultivariable HR (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-Value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor site\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTongue (179) vs Buccal mucosa (189)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61 vs 69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.2 (0.9\u0026ndash;1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor volume\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026le;\u0026thinsp;15 cm\u0026sup3; (246) vs\u0026thinsp;\u0026gt;\u0026thinsp;15 cm\u0026sup3; (237)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72 vs 58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.5 (1.1\u0026ndash;2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTreatment delay (TTI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026le;\u0026thinsp;8 weeks (274) vs\u0026thinsp;\u0026gt;\u0026thinsp;8 weeks (209)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75 vs 55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.6 (1.1\u0026ndash;2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epT category\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT1\u0026ndash;2 (254) vs T3\u0026ndash;4 (229)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e78 vs 52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.8 (1.3\u0026ndash;2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epN category\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN0 (261) vs N+ (222)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74 vs 56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.7 (1.2\u0026ndash;2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDepth of invasion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026le;\u0026thinsp;10 mm (268) vs\u0026thinsp;\u0026gt;\u0026thinsp;10 mm (215)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e73 vs 59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.4 (1.0\u0026ndash;1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePerineural invasion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAbsent (412) vs Present (71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70 vs 49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.5 (1.0\u0026ndash;2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLymphovascular invasion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAbsent (435) vs Present (48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69 vs 47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.4 (0.9\u0026ndash;2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWorst pattern of invasion (WPOI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026ndash;3 (308) vs 4\u0026ndash;5 (175)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72 vs 53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.6 (1.2\u0026ndash;2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStage migration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo (336) vs Yes (147)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71 vs 55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.5 (1.1\u0026ndash;2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis prospective study provides one of the most comprehensive evaluations to date of the natural progression and tumor kinetics of oral squamous cell carcinoma (OSCC) using serial imaging. By integrating volumetric data, doubling time analysis, and stage migration with survival outcomes in a large cohort of 483 patients, we demonstrate that OSCC exhibits biologically aggressive progression even over short treatment delays. The median tumor volume doubling time (TVDT) ranged from 6\u0026ndash;10 weeks, with tongue primaries and poorly differentiated tumours growing most rapidly. These findings have both biological and practical implications, highlighting the importance of timely intervention and the potential role of volumetric kinetics as an independent prognostic variable.\u003c/p\u003e\u003cp\u003eTreatment delay has long been recognized as detrimental in head and neck cancers, yet its biological underpinning has rarely been quantified. Most prior studies are retrospective, administrative, or population-based, relying on registry data that link delays to survival but without validating whether measurable disease progression occurs during that interval. (\u003cspan additionalcitationids=\"CR13 CR14\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) The present study bridges that gap, prospectively documenting tangible volumetric growth and stage migration during pre-treatment waiting periods. The observed median growth rate of 7.3% per week, corresponding to near doubling within two months, mirrors theoretical models proposed by Schwartz and colleagues for exponential tumor kinetics. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eThis rate of progression underscores that OSCC is far from indolent; even modest delays can have clinically meaningful consequences for resectability and prognosis. Our findings affirm earlier reports that tumor volume and treatment delay independently influence outcomes. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) However, by explicitly calculating TVDT, we demonstrate a quantifiable biological parameter that links these two phenomena. Patients with TVDT\u0026thinsp;\u0026le;\u0026thinsp;8 weeks had nearly 16% lower two-year overall survival and a 1.7-fold higher risk of death independent of T-category, N-category, or perineural invasion. These data suggest that tumor kinetics capture an element of intrinsic aggressiveness not reflected in static TNM classification. Incorporating volumetric progression and TVDT into future staging or prognostic models could therefore improve risk stratification and guide personalized treatment scheduling.\u003c/p\u003e\u003cp\u003eDistinct subsite-specific patterns of spread were evident and reinforce known anatomic pathways. Tongue tumours predominantly extended along the antero-posterior axis, with only one-fifth crossing the midline over two to three months, consistent with the restraining effect of the midline raphe. Buccal mucosa lesions expanded laterally into the alveolus and masticator space, while retromolar trigone tumours favoured superior extension into the infratemporal fossa. Retroantral space involvement, though less common, was linked to significantly accelerated growth rates. These observations emphasize the heterogeneity of OSCC behaviour and have practical implications for preoperative imaging, surgical planning, and adjuvant field delineation. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eThe phenomenon of stage migration in this cohort\u0026mdash;observed in nearly one-third of patients\u0026mdash;translated directly into changes in management. Patients who were initially operable with limited resections often required more extensive composite resections, segmental mandibulectomy, or free-flap reconstruction after interval progression. In certain cases, progression rendered disease unresectable. Thus, treatment delay not only worsens survival but also increases surgical morbidity, functional impairment, and economic burden. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) These findings reinforce the need for institutional protocols that prioritize surgical scheduling based on tumor kinetics rather than chronological order alone.\u003c/p\u003e\u003cp\u003eThe concept of TVDT offers a dynamic, easily interpretable metric of tumor aggressiveness. It allows clinicians to estimate the biological impact of delay using a quantifiable measure rather than intuition alone. A shorter TVDT reflects high proliferative potential, possibly related to underlying molecular events such as p53 mutations, EGFR overexpression, or hypoxia-inducible signalling, which warrant further investigation. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) Future multi-institutional studies could explore the molecular correlates of radiologically derived TVDT, establishing it as a surrogate imaging biomarker of aggressiveness in OSCC.\u003c/p\u003e\u003cp\u003eOur analysis also illustrates that tumor growth is not strictly linear. Although we calculated weekly percentage changes and doubling times assuming uniform growth for practicality, the biological reality is likely nonlinear, with an early exponential phase followed by a plateau. The relatively short observation intervals (median seven weeks) minimize this deviation, but future work using serial imaging at multiple points could refine kinetic modelling further. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eA notable methodological feature of this study is the deliberate separation of radiographic and pathologic parameters. Radiographic tumor thickness (RTT) and radiologic extranodal extension (rENE) were recorded objectively but interpreted cautiously, acknowledging that these measures have not been uniformly validated against pathology in OSCC. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) Pathologic depth of invasion (DOI) and ENE, where available, were used for prognostication. RTT nonetheless offers a pragmatic alternative in preoperative settings, providing a reproducible measure to track interim progression. A strong correlation between RTT and DOI, once established prospectively, could make imaging-derived metrics invaluable for dynamic risk assessment.\u003c/p\u003e\u003cp\u003eThe limitations of the current study include: (i) although prospectively designed, it represents experience from a single high-volume cancer centre, which may limit generalizability; (ii) despite standardized imaging protocols, minor variations in contrast timing, slice reconstruction, and contouring could influence volumetric accuracy; (iii) approximately 12% of screened patients who progressed to unresectable disease before definitive treatment were excluded from survival analyses, possibly underestimating the full impact of delay; (iv) radiologic parameters such as RTT and rENE require further validation against pathologic gold standards; (v) our modelling assumes linear growth between imaging points, which may simplify complex biological kinetics.\u003c/p\u003e\u003cp\u003eDespite these limitations, the strengths of this work are significant. It is one of the largest prospective datasets to examine tumor kinetics in OSCC, employs standardized contouring by a multidisciplinary team, and integrates volumetric kinetics with survival endpoints. The study provides direct biological evidence for the clinical observation that OSCC can change substantially over short intervals.\u003c/p\u003e\u003cp\u003eTreatment delay should not be viewed merely as a logistical constraint but as a biological and systemic issue. In public tertiary centres, delays arise from both patient-related factors\u0026mdash;financial limitations, social obligations, treatment hesitancy\u0026mdash;and system-level constraints such as overburdened operating schedules, limited surgical slots, and pandemic-era backlogs. Our findings quantify the biological cost of these delays: even an additional month between diagnosis and surgery can result in measurable tumor volume increase, stage migration, and compromised survival. In contexts where complete elimination of delay is unrealistic, triaging based on biological risk\u0026mdash;such as high-volume, short-TVDT tumours\u0026mdash;may help allocate limited resources most effectively. Future directions include multicentric validation, incorporation of MRI-based radiomics for microstructural assessment, and exploration of whether kinetic metrics can predict treatment response or recurrence patterns. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eOSCC exhibits rapid volumetric progression, with tumours doubling in size within 6\u0026ndash;10 weeks. Shorter tumor volume doubling time, advanced stage, and treatment delay beyond eight weeks independently predict poorer survival. Tumour kinetics thus serve as a dynamic biomarker that transcends static staging, offering actionable information for clinicians and policymakers. Integrating TVDT and volumetric growth into prognostic frameworks could improve patient counselling, surgical prioritization, and health system planning. At a broader level, this study reinforces the urgent need for institutional and policy-level strategies to minimize diagnostic and treatment delays, thereby improving both survival and quality of life in patients with oral cancer.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eFunding statement\u003c/p\u003e\n\u003cp\u003eNil. No funding was obtained from any sources.\u003c/p\u003e\n\u003cp\u003eConflict of Interest statement\u003c/p\u003e\n\u003cp\u003eNil. None of the authors have any conflict of interest to declare.\u003c/p\u003e\n\u003cp\u003eEthics Approval Statement\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study has been approved by the Institutional Ethics Committee\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eData Availability Statement\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eData will not be made available as per the Institute’s Ethic Committee Approval letter\u003c/p\u003e\n\u003cp\u003eAuthors contribution statement\u003c/p\u003e\n\u003cp\u003eDr. Arjun Gurmeet Singh (Corresponding author)*:\u0026nbsp;Study concept, design, data collection and analysis, manuscript drafting and revision\u003c/p\u003e\n\u003cp\u003eDr. Abhishek Mahajan:\u0026nbsp;Study concept, design, data analysis, manuscript drafting and revision\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDr. Shwetabh Sinha:\u0026nbsp;Data collection and analysis, manuscript drafting and revision\u003c/p\u003e\n\u003cp\u003eDr. Rathan Shetty:\u0026nbsp;Data collection and analysis, manuscript drafting and revision\u003c/p\u003e\n\u003cp\u003eDr. Samarprita Mohanty:\u0026nbsp;Data collection and analysis, manuscript drafting and revision\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDr. Anuj Kumar:\u0026nbsp;Data collection and analysis, manuscript drafting and revision\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDr. Nivedita Chakrabarty:\u0026nbsp;Data analysis, manuscript drafting and revision\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDr. Poonam Joshi:\u0026nbsp;Manuscript drafting and revision\u003c/p\u003e\n\u003cp\u003eDr. Sudhir Nair:\u0026nbsp;Manuscript drafting and revision\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDr. Sarbani Ghosh Laskar:\u0026nbsp;Manuscript drafting and revision\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDr. Kumar Prabhash:\u0026nbsp;Manuscript drafting and revision\u003c/p\u003e\n\u003cp\u003eDr. Pankaj Chaturvedi: Study concept, design, data collection and analysis, manuscript drafting and revision\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eFerlay, J. et al. in \u003cem\u003eGlobal Cancer Observatory: Cancer Today\u003c/em\u003e. (eds Lyon) (International Agency for Research on Cancer, 2024).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBray, F., Laversanne, M., Weiderpass, E. \u0026amp; Soerjomataram, I. The ever-increasing importance of cancer registries in low- and middle-income countries. \u003cem\u003eCancer Epidemiol.\u003c/em\u003e \u003cb\u003e71\u003c/b\u003e, 101858 (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSankaranarayanan, R., Ramadas, K., Amarasinghe, H., Subramanian, S. \u0026amp; Johnson, N. Oral cancer: Prevention, early detection and treatment. \u003cem\u003eBull. World Health Organ.\u003c/em\u003e \u003cb\u003e93\u003c/b\u003e (9), 614\u0026ndash;622 (2015).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWarnakulasuriya, S. 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External validation of a prognostic radiomic signature in head and neck squamous cell carcinoma. \u003cem\u003eRadiother Oncol.\u003c/em\u003e \u003cb\u003e117\u003c/b\u003e (3), 427\u0026ndash;432 (2015).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Oral cancer, tumour volume, natural progression, AJCC classification, treatment delay","lastPublishedDoi":"10.21203/rs.3.rs-7855507/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7855507/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis prospective cohort study quantified the biological impact of treatment delay in oral squamous cell carcinoma (OSCC) through tumour kinetics. Between July 2020 and December 2023, 483 patients with treatment-naïve OSCC, Mumbai, underwent two pre-surgery cross-sectional imaging studies at least three weeks apart. Gross tumour volume (GTV) was measured to calculate weekly percentage growth and tumour volume doubling time (TVDT) using the Schwartz exponential model. The median interval between scans was 7.1 weeks (IQR, 5.9–9.4). Median GTV increased from 12.9 cm³ (IQR, 8.1–20.2) to 19.4 cm³ (IQR, 12.3–28.6), a 7.3% median weekly rise corresponding to a TVDT of 7.9 weeks. Tongue tumours grew fastest (9.6% per week; TVDT 6.2 weeks). Stage migration occurred in 30%, leading to more extensive resections in 28%. At 25 months’ median follow-up, 2-year overall survival (OS) and disease-specific survival were 67% and 73%, respectively. Patients with TVDT ≤8 weeks had lower OS (58% vs 74%, p=0.002). On multivariable analysis, TVDT ≤8 weeks, treatment delay \u0026gt;8 weeks, advanced T/N-category, and perineural invasion independently predicted worse outcomes. OSCC doubles in volume within 6–10 weeks, and tumour kinetics offer a quantifiable marker of aggressiveness that should inform scheduling and prognosis.\u003c/p\u003e","manuscriptTitle":"Tumor Growth Kinetics and the Biological Cost of Treatment Delay in Oral Cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-14 07:09:58","doi":"10.21203/rs.3.rs-7855507/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bd437d20-beac-4b95-88aa-7b5630eb87ae","owner":[],"postedDate":"November 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":57672867,"name":"Biological sciences/Cancer"},{"id":57672868,"name":"Health sciences/Oncology"}],"tags":[],"updatedAt":"2025-12-19T13:39:40+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-14 07:09:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7855507","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7855507","identity":"rs-7855507","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}