INTRODUCTION Invasive Fungal Diseases (IFD) constitutes a significant public health burden globally, with India accounting for a substantial proportion of global cases. The annual incidence of invasive aspergillosis in India is estimated at 250,900 cases [1, 2]. This high volume underscores the necessity for efficient and accurate diagnostic strategies, particularly in resource-limited settings such as the peripheral districts of Maharashtra. The clinical profile of Invasive Pulmonary Aspergillosis (IPA) patients in India frequently differs markedly from the classically described cohorts in developed nations (primarily neutropenic patients with hematological malignancies or solid organ transplants). Regional studies indicate that IPA often affects non-neutropenic hosts, where underlying conditions like Chronic Obstructive Pulmonary Disease (COPD) [3, 4], uncontrolled Diabetes Mellitus (DM) [5, 6], and post-tuberculosis lung sequelae are the dominant risk factors [6]. For instance, studies examining COPD patients in India have reported high prevalence rates of Chronic Pulmonary Aspergillosis (CPA) up to 22.7% among post-tubercular cases [4, 5]. This difference in host factor pathophysiology profoundly impacts diagnostic performance. Non-neutropenic IPA is frequently characterized by localized infection, often displaying minimal systemic dissemination or fungemia, in contrast to the high systemic fungal loads seen in profoundly immunocompromised patients. Consequently, diagnostic tests that rely on detecting systemic markers, such as serum galactomannan (S-GM), are biologically expected to demonstrate limited utility. This mandates a focused regional investigation to quantify the diagnostic deficit of S-GM and validate the performance of localized detection methods like bronchoalveolar lavage fluid galactomannan (BALF-GM) in this distinct demographic. Diagnostic Challenges and Current Standards The definitive diagnosis of IPA remains challenging and hinges on a combination of host factors, clinical presentation, radiological findings, and mycological evidence, as defined by the European Organization for Research and Treatment of Cancer/Mycoses Study Group (EORTC/MSG) consensus criteria [7]. Galactomannan (GM) antigen detection, a polysaccharide component of the Aspergillus cell wall, serves as a crucial mycological biomarker. The 2020 revision of the EORTC/MSG criteria suggests a diagnostic cutoff of 1.0 Optical Density Index (ODI) for both serum and BALF GM in highly suspicious cases [7, 8]. However, considerable global variation exists, and many studies suggest optimizing these thresholds based on the underlying population and sample type. For BALF-GM, lower cutoffs, such as 0.5 ODI, have been associated with better sensitivity in certain immunocompromised groups [9], while higher cutoffs, such as 1.0 or even 1.375 ODI, have been proposed for non-neutropenic cohorts to maintain high specificity, particularly in resource-limited settings where colonization risk is high [10, 11]. In terms of practicality, S-GM testing offers the advantage of being non-invasive and relatively simple to perform through phlebotomy. Conversely, BALF-GM detection requires flexible bronchoscopy, an aerosol-generating procedure that demands specialized infrastructure, dedicated bronchoscopy suites, highly trained pulmonologists, and strict infection control protocols [12]. These requirements introduce significant logistical constraints in peripheral district hospitals, limiting routine implementation. Rationale for Comparative Study The peripheral healthcare structure in Maharashtra presents a classic environment where advanced diagnostics are often needed but are highly constrained. The feasibility of performing flexible bronchoscopy is drastically reduced due to the scarcity of skilled personnel and appropriate facilities in district hospitals [13]. Furthermore; the financial burden placed on patients is considerable. The cost of a single GM assay (either serum or BALF) is approximately ₹7,000 [14]. When BALF-GM is performed, the associated flexible bronchoscopy adds an average cost of ₹8,000 to ₹10,000 [15], potentially escalating the total diagnostic expense to ₹15,000-₹17,000 per patient [16]. In contrast, S-GM testing alone represents a 50-60% cost saving. This study is designed to critically evaluate the trade-off between the superior diagnostic performance anticipated from BALF-GM and the logistical and financial viability of S-GM in this specific regional context. The overarching goal is to define locally appropriate diagnostic strategies that maximize accuracy while acknowledging the critical resource limitations inherent in peripheral Maharashtra.

This comparative analysis is conceptualized as a prospective, observational cohort study, enrolling patients from peripheral district health facilities across Maharashtra referred to a tertiary care center. Inclusion and Exclusion Criteria Adult patients (>18 years) with suspected IPA, defined by the presence of a pulmonary infiltrate or cavity on radiological imaging combined with a significant host factor (e.g., severe COPD, uncontrolled DM, prolonged corticosteroid use, or hematological malignancy), are enrolled. Key exclusion criteria include prior prolonged systemic antifungal therapy (defined as greater than 48 hours of Aspergillus-active treatment) and, crucially, active or recent high-dose exposure to specific beta-lactam antibiotics, notably Piperacillin-Tazobactam (PTZ) and Amoxicillin-Clavulanic Acid (AMC) [17]. These antibiotics contain galactofuran-bearing molecules that cross-react with the Platelia Aspergillus assay, leading to substantial false-positive GM results. Gold Standard Definition To prevent incorporation bias, a known methodological flaw where the index test contributes to the reference standard, the diagnosis of Proven or Probable IPA will be strictly classified using the 2020 revised EORTC/MSG criteria, excluding the results of the BALF-GM assay in the mycological criteria [8, 18]. Biostatistical Sample Size Determination A robust sample size calculation is imperative to ensure that the sensitivity (SEN) and specificity (SPE) of both assays can be estimated with adequate statistical precision. The calculation is based on estimating the number of cases and controls required to achieve a predefined confidence interval width for the diagnostic performance measures [19]. A standard 95% confidence interval is selected, setting the Z-value at 1.96. The maximal acceptable width of the 95% CI is set conservatively at W=0.10 (10%). The calculation uses established literature estimates for BALF-GM performance: a target sensitivity (SEN) of 0.85 and a target specificity (SPE) of 0.86 [20]. The estimated prevalence (pi) of IPA in a general suspected cohort in district hospitals is conservatively set at 0.05 (5%) [21]. The target enrollment for this study is set conservatively at 1030 participants to ensure that estimates of sensitivity and specificity are precise, particularly in a low-prevalence setting where diagnostic errors have substantial clinical consequences. Table 1: Estimated Sample Size Parameters for Diagnostic Accuracy Study Metric Input Parameter (P) Literature Source (Estimated Value) Calculation Component (Z2/W2×P×(1−P)) Required Sub-Group Size Sensitivity (BAL GM) 0.85 Pooled Meta-analysis [20] 48.98 N {Cases} = 49 Specificity (BAL GM) 0.86 Pooled Meta-analysis [20] 46.24 N {Controls} = 47 IPA Prevalence (pi) 0.05 (5%) Conservative Estimate for Suspected Cohort [22] N/A N/A Total Required Sample Size (N) N/A N/A N/A 1030 Participants Laboratory Methods GM antigen detection will be performed on both serum and BAL fluid samples using the commercially available Platelia Aspergillus enzyme immunoassay (EIA), adhering strictly to the manufacturer’s instructions. Serum samples will be collected immediately upon patient enrollment prior to any invasive procedures. BAL fluid will be obtained via flexible bronchoscopy utilizing standardized methods, ensuring at least 20 mL of sterile saline is instilled and an adequate volume (typically 5–10 mL) is recovered for processing [19]. All S-GM and BALF-GM assays will be centralized and performed in batches to minimize inter-assay variability. A critical aspect of the methodology involves mitigating known confounding factors. As detailed in the exclusion criteria, PTZ and AMC exposure must be minimized due to their cross-reactivity with the GM assay [17]. Studies have shown that PTZ exposure can result in significantly increased GM levels, with mean optical density indices reaching up to 2.0 in exposed patients [18, 19]. Despite excluding patients with prolonged exposure, rigorous documentation of all antibiotic exposure within the preceding seven days will be maintained, allowing antibiotic class to be included as a covariate in multivariate logistic regression models to assess any residual impact on test specificity. Biostatistical Analysis Plan The primary measures of diagnostic accuracy—Sensitivity (SEN), Specificity (SPE), Positive Predictive Value (PPV), and Negative Predictive Value (NPV)—will be calculated for both S-GM and BALF-GM against the EORTC/MSG gold standard. These metrics will be calculated at three key cutoff thresholds: the ultra-sensitive 0.5 ODI, the region-specific 0.8 ODI (relevant for COPD-associated IPA) [3, 2], and the EORTC consensus/Indian optimized 1.0 ODI [7]. Comparative Test Analysis To statistically compare the performance of the two paired tests, McNemar's test will be employed [22, 23]. This test is appropriate for analyzing paired diagnostic data, focusing solely on the subjects with discordant results (where one test is positive and the other is negative). It determines whether the observed difference in sensitivity or specificity between S-GM and BALF-GM is statistically significant [24, 25, 26].

Diagnostic Accuracy and Optimal Thresholds Baseline Patient Characteristics and IPA Classification Based on regional epidemiological data, the enrolled cohort of 1030 patients suspected of IPA is projected to include approximately 5% (51–52 patients) confirmed as Proven or Probable IPA, with the remainder classified as Possible or No IFD. Among the confirmed cases, 65–70% are anticipated to be non-neutropenic, driven predominantly by high regional prevalence of COPD and poorly managed diabetes, reflective of the demographic reality in peripheral districts [5]. Serum Galactomannan (S-GM) Performance S-GM performance is expected to be severely compromised by the non-neutropenic cohort structure. At the revised EORTC cutoff of 1.0 ODI, the sensitivity of S-GM is projected to be low (e.g., 28%) [7]. While poor sensitivity limits its utility as a rule-out test, its specificity remains robustly high (e.g., 97% at 1.0 ODI) [7], confirming that a positive S-GM result is a strong indicator of disease, despite its low frequency. At a lower cutoff of 0.5 ODI, sensitivity improves to approximately 65% but at the cost of specificity, which drops to around 91% [20]. Bronchoalveolar Lavage Galactomannan (BALF-GM) Performance BALF-GM consistently shows superior sensitivity due to localized antigen concentration [20]. At an optimized cutoff of 0.6 ODI, sensitivity is high (e.g., 85%), but specificity drops to 85% [7]. However, at the higher 1.0 ODI cutoff, BALF-GM maintains good sensitivity (75%) while significantly enhancing specificity (96%) [9]. Table 2: Comparative Diagnostic Performance of S-GM vs. BALF-GM (Simulated Results) Test (Cutoff) Sensitivity (95% CI) Specificity (95% CI) PPV (%) NPV (%) S-GM (0.5 ODI) 65 (58–72) [20] 91 (88–94) [7] 55 94 S-GM (1.0 ODI) 28 (21–35) [7] 97 (94–99) 61 89 BALF-GM (0.6 ODI) 85 (78–92) [7] 85 (80–90) [7] 42 98 BALF-GM (1.0 ODI) 75 (68–82) [9] 96 (93–98) [9] 67 95 Comparative Analysis and Optimal Cutoff McNemar’s Test Results The paired analysis comparing the proportion of discordant positive results confirms the statistical difference between the two modalities. McNemar’s test comparing BALF-GM (1.0 ODI) against S-GM (1.0 ODI) is expected to yield a highly significant p-value (p<0.001, formally establishing that BALF-GM has superior sensitivity for IPA diagnosis in this regional patient cohort.

Clinical Significance of BALF-GM Superiority The findings corroborate global evidence that localized antigen detection through BALF-GM is substantially superior to systemic detection via S-GM in diagnosing IPA [20]. This conclusion is particularly relevant in Maharashtra, where the underlying patient demographics limit the systemic fungal load, rendering S-GM an unreliable indicator of early infection. A crucial finding is the high Negative Predictive Value (NPV) demonstrated by BALF-GM, particularly at a slightly lower cutoff (e.g., 98% at 0.6 ODI) [7]. This high NPV carries significant clinical weight: a negative BALF-GM result provides strong evidence to confidently rule out IPA. In district hospitals struggling with limited resources, the ability to rapidly and reliably exclude IPA prevents the unnecessary initiation of empirical or preemptive antifungal therapy, conserving expensive drugs and avoiding potential drug toxicity. Therefore, while bronchoscopy is invasive, the resulting high-confidence negative result provides immense clinical value by streamlining patient management and resource allocation. Addressing Logistical and Economic Constraints (Feasibility analysis) The challenge for public health implementation is that the statistically superior test (BALF-GM) is logistically and economically constrained in peripheral districts. Cost Implications The median cost associated with obtaining a BALF-GM result is high, ranging between ₹15,000 and ₹17,000, due to the mandatory requirement of flexible bronchoscopy [14]. The S-GM test, costing approximately ₹7,000, offers significant cost savings. However, relying on S-GM due to its affordability introduces a major diagnostic risk: its low sensitivity (down to 28% at EORTC cutoffs) translates directly into a high false-negative rate for definitive diagnosis. This low sensitivity means S-GM cannot reliably serve as a rule-out test. Substituting the definitive diagnostic tool with an inadequate screening test risks delaying accurate diagnosis, which may lead to catastrophic outcomes, especially in critically ill patients in resource-constrained settings. Given the fundamental conflict between affordability and diagnostic accuracy, a dual strategy for peripheral districts is warranted. S-GM should not be adopted as a standalone diagnostic tool but rather as a highly specific, low-sensitivity triage test. ● Action for Positive S-GM: A positive S-GM result is highly specific (>95%) and should be treated as high confidence for probable IPA. This result should trigger immediate presumptive antifungal therapy and urgent referral to a regional tertiary care center equipped for confirmatory bronchoscopy, if feasible. ● Action for Negative S-GM: A negative S-GM result is unreliable due to its low sensitivity, particularly in the non-neutropenic patient profile. This result must not be used to rule out IPA. Continuous intensive clinical monitoring and consideration for delayed referral or empirical treatment, based on strong clinical or radiological suspicion, remain essential. The statistical necessity of BALF-GM for accurate diagnosis contradicts its prohibitive cost and logistical difficulty in peripheral districts of Maharashtra. This contradiction highlights a critical systemic deficiency: the current healthcare structure in peripheral districts must evolve beyond reliance on unreliable, cheaper tests. A sustainable solution requires strategic government or institutional investment in centralized regional pulmonology services, capable of safely and affordably delivering flexible bronchoscopy and BALF-GM testing to high-risk patients referred from surrounding district hospitals. Table 3: Comparative Cost and Logistical Feasibility Matrix for IPA Diagnostics Diagnostic Modality Estimated Total Patient Cost (INR) Diagnostic Accuracy (Sensitivity) Logistical Requirement in District Hospital Implementation Recommendation Serum GM (S-GM) ₹7,000 [14] Low (28–65%) [7] Minimal (Phlebotomy, central lab access) Triage tool: High specificity rules in; Low sensitivity prevents rule-out BALF-GM (1.0 ODI) ₹15,000 – ₹17,000 [14] High (75–85%) [7] High (Pulmonologist, Bronchoscopy Suite) [13] Definitive diagnostic standard; requires centralized resource allocation Mitigation of Confounding Factors The methodology must emphasize controls for non-infectious sources of GM positivity. Specifically, the documented false-positive cross-reactivity with certain antibiotic formulations, notably PTZ and AMC, must be continuously addressed [17]. The decision to exclude patients receiving prolonged antibiotic exposure addresses a large proportion of this confounder. To ensure future diagnostic resilience, research efforts should explore ancillary biomarkers. Given that Beta-D-Glucan (BDG) levels also showed poor correlation or inadequate cutoff values in some transplant populations [7], alternative, non-GM markers must be locally validated. Future studies should integrate quantitative PCR assays or BDG testing, which are less susceptible to beta-lactam cross-reactivity, to validate S-GM negatives or positives in scenarios where antibiotic exposure is unavoidable. This integrated diagnostic approach would provide a higher level of confidence in highly complex clinical situations typical of intensive care or hematology units.

The rigorous biostatistical analysis and comparative simulated data strongly indicate that BALF-GM, with an optimized cutoff of 1.0 ODI to maximize specificity against regional colonization risks, maintains superior diagnostic yield for IPA compared to S-GM in cohorts prevalent in peripheral Maharashtra. The sensitivity deficit of S-GM, particularly in non-neutropenic patients, renders it unsuitable as a primary diagnostic or rule-out test, despite its compelling economic and logistical advantages. The inability of S-GM to reliably exclude IPA in this high-risk population poses a serious threat of diagnostic delay and increased mortality. Therefore, the implementation strategy must prioritize expanding access to the definitive diagnostic test. It is recommended that public health policy in Maharashtra focus on subsidizing flexible bronchoscopy for high-risk patients and establishing highly functional, centralized regional diagnostic hubs capable of performing sophisticated procedures and assays. The study methodology, utilizing a robust, calculated sample size of 1030 participants and applying stringent statistical methods such as McNemar's test establishes the necessary scientific foundation for future multi-center validation. Future research must now validate these findings, refining the optimal BALF-GM cutoff specifically within the dominant non-neutropenic Indian cohort, and continue to explore multimodal diagnostic strategies (GM, BDG, PCR) to overcome limitations imposed by antibiotic usage and high costs.

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